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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0003.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0003.csv
index 7e78a2761a851fa9d51ae6237da8752f10406bc7..9f693933ec39285d4fa14905861174f1578e561d 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0003.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0003.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0004.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0004.csv
index aa05c776c6359c71e8e466686635e6606bb192bd..538656f53a9eca7f17d6080d8dd306c239b79e8e 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0004.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0004.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0005.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0005.csv
index 0dfd8d314715476f5ced7aa2762ada1553c17786..4fe164870ce6b2938a96454ecc245967d7b247c3 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0005.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0005.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0006.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0006.csv
index 5c09dbd1f3d8cd70e149a71a57dd9d8534e76af8..9047154b7ad7ab8e2ecd4ba388550266f0215c06 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0006.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0006.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0007.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0007.csv
index e9f7dbda4adb7a7a440fd472e631a867b39d9351..78cb270e2ba78fe3b86fa8611b52943f74644771 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0007.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0007.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0008.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0008.csv
index 4f5c2649312fc739233f0d51ddb38980a3bf82d4..eab96394c4e7bc7836ec7a82e263dd4b68f14b62 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0008.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0008.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0009.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0009.csv
index 810389cb70b277366d9e6a0d6de54aa0ebdf8f65..5e3c67fb46e54c099a932be45d7ca7445967f45a 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0009.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0009.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0010.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0010.csv
index f18a61045566f031af73895af5a2932678daa5cc..aa4c152e3bebda655e536cfe9a7c0d6eb576d3a8 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0010.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0010.csv
@@ -1,88 +1,318 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0011.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0011.csv
index 93ca73360f27416e96b95d1105314d20f31802fe..44c227519ff4c9cb642233cac73efec80ae81df2 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0011.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0011.csv
@@ -1,101 +1,277 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0012.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0012.csv
index 0c7b8b191dbadf2cae77d0355d79236e45ae3b4b..821c019be09501bcf4d843632f1101049865039b 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0012.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0012.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0013.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0013.csv
index 0bce2f31a6db3dba3f1cc6a423b120938fc3d17e..e1a8f1c1bdff9a9b2903cccfc2e2a3363ebab79d 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0013.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0013.csv
@@ -1,100 +1,262 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0014.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0014.csv
index cb050df4e9f37dafa9ed219bd0d1bbbbc9eeaa80..b05ba6a3e8900363921ede25c2be0c76bb87a251 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0014.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0014.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0015.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0015.csv
index 63ad6366c9598a0a94c05cec26ed397b0e9330f9..e800c12cb1cf7f640ca5b1588799bd8ce5a6f7b4 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0015.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0015.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0016.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0016.csv
index 619e5570c1698c6bac2f12f814012b7694e65a0c..e8a627e03969a501d8bafaf71eb5b996159deba0 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0016.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0016.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0017.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0017.csv
index 11d4074cf7cbd5094c16909754e5af295c6970be..3d0a7f761d8bce6335c3a800b08d2b9a36de8b3a 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0017.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0017.csv
@@ -1,110 +1,194 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0018.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0018.csv
index 22335263e4c53f308362237e440b5cf11465f378..9bf44c6d9b20eebf7c33150e3dfb78b206afb846 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0018.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0018.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0019.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0019.csv
index 7e0d16d9c885003d78c94d1f529ea8c0c88d50b5..38e591ddeeabe9842154bda5bc4b5e2b5b112d1a 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0019.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0019.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0020.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0020.csv
index 7319bed1d6e06a3721deaf63322e3841ec313911..c68f187131469ca16ce04418ad537379cdbc6bb4 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0020.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0020.csv
@@ -1,76 +1,282 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0021.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0021.csv
index 8925c77e1aac1234c2f349983b2eefc670b8c8c9..0312843d2c6c0ebdace49f7e41448f5991351b6a 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0021.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0021.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0022.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0022.csv
index d04e6516e50ff0d622214f2cbde6945e1d50a39a..70a2b735964f505fba513326e2a9f9d14c170e96 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0022.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0022.csv
@@ -1,74 +1,200 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0023.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0023.csv
index fa26869c243ab1e0ab1b7df5f2cc8acba8ac7eaf..85d3faaa08994ecd5c34bad682646cf95c946d6a 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0023.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0023.csv
@@ -1,68 +1,207 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0024.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0024.csv
index f1dfcb35d8010c5e91dfff9ea29055f6c8e33f1c..ebd9a4cd8c51fe6d5e510b3429c24daa82fe2d6a 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0024.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0024.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0025.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0025.csv
index ba800ec0cad12965bd498c23ee868480b7ce46af..15c68dd49bce3c1aee60a74215346f4deb3a4a50 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0025.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0025.csv
@@ -1,106 +1,220 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0026.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0026.csv
index d96fea3c234bbcd25b65dc6548bc84e38bbf7690..1e653ea0a97d2b578e28c4956e005d72ee4cedc2 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0026.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0026.csv
@@ -1,116 +1,100 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0027.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0027.csv
index 439162836101aac386471853f2731585b7a77ce5..95c73f3fe751015b19e1fa445e76781fef8f0058 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0027.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0027.csv
@@ -1,104 +1,153 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0028.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0028.csv
index d604928669cf2bac2f98f82314b721e65d435a34..0683ec528b216b38ae0a50941a4e8456b2512faa 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0028.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0028.csv
@@ -1,107 +1,86 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0029.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0029.csv
index e49d565315fae5d4d020eaeccfc421650573ad05..799d15280060b57d093c7e6179a4256c11c48396 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0029.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0029.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0030.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0030.csv
index 551d6bdb8b0ec2e9513de9d9b0436dd39a149773..9440b6c409396f74cb517af3500cb3237a732f75 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0030.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0030.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0031.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0031.csv
index 98b1e6e06856023f54025f32300a823abeb218e9..b16540301927811a0b0d1b44e315877eaa3fe425 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0031.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0031.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0032.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0032.csv
index 245f4932942dbfbc2135be5fe3e08b594a7fb413..fa51d7e72b2bf9fccb295b530cfca1a581b4313c 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0032.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0032.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0033.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0033.csv
index 3b11db1fd7ddd16ed024bfbf22d70b1fd3b28a8b..95b596a946c3943edf4fd969775d2ca275e4d5fc 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0033.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0033.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0034.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0034.csv
index 3c6e5098c6434d6c774d4f57da9dea1399b20d15..c76bc576bc3c202ec931b006a46b7eadae18ad99 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0034.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0034.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0035.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0035.csv
index 11923cd0b97a5ff0971a5e5e2c08216d155bb98c..83d840e0f7d30dfb55ed2860f92497f90d73cc4f 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0035.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0035.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0036.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0036.csv
index e6edcfcefa99e40a279a25266375e43c7deff0cf..8078f6e4126e0110aa9a01888832a0e852508267 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0036.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0036.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0037.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0037.csv
index 11f4de7dc3c9d66ca4f555b65767ddbb50bb3654..25458359113732413aa3fe420e1e1b025a613a7a 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0037.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0037.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0038.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0038.csv
index f98c70e0700b580012ef45d211cde4b4cfa19a3f..3875596b5943c010b6fbc2073308a7ab5a4df192 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0038.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0038.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0039.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0039.csv
index 1af747ec93e4244d8ee80fcca404e2e549ddc6a5..c6045a570a1b54ebe83e4ee797669663447f4e55 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0039.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0039.csv
@@ -1,90 +1,242 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0040.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0040.csv
index aebead2e6b44533bb5e1b0e51bb9784886162c14..047dd671ef917af2040f11c252b7adb0cc45aaf5 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0040.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0040.csv
@@ -1,79 +1,152 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0041.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0041.csv
index c297e1e8c6966eafe4a65554c73eca9427937f16..870ea00cf6bfeda2683ffa4ce2f432a42a28e289 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0041.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0041.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0042.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0042.csv
index 0b2b52059f019d8d09bd2f40742f86cab3b7523b..3db99198e153d9c695f98bb3d28553e22935769c 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0042.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0042.csv
@@ -1,68 +1,90 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0043.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0043.csv
index 79f2fb786fbe6aa90d0340d2cd838b0d67e7b2da..6ac1adb62dd976cc5e3801114cde0149f267e011 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0043.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0043.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0044.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0044.csv
index 440f9a8689d267cef635da7149a061fc9b8d8063..06891d4e24db9cf6c72a04f0c1529bd35fdbaf1a 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0044.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0044.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0045.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0045.csv
index 71d25e72c77138eb51240687c162e789745de926..f2acfe96f5a346078a9d503a2b6e4686b1e62321 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0045.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0045.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0046.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0046.csv
index e13193fac711e1320ab3ba47bad9d6cffb74aaa6..b42d624990dd0fdf0b31c2195336b384f3335659 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0046.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0046.csv
@@ -1,74 +1,164 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0047.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0047.csv
index bb6572ed5a4a100ee68fa9e8b80fa1e6b2df96cb..64d33765588ed9a7fe03026c013705421602e6fb 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0047.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0047.csv
@@ -1,68 +1,258 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0048.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0048.csv
index 594e01b5db10cf0afb2b73b6ab865ca944653760..1ab4888b769cc4c0d00d3e5bd46d390ea29f3e48 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0048.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0048.csv
@@ -1,77 +1,180 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0049.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0049.csv
index c5ddfec95f7c4cbf1aac4b76bc0d16903dd0b56d..9b81cbe43bb352fd77b85c1e2ef82de1eb9f23ca 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0049.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0049.csv
@@ -1,70 +1,189 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0050.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0050.csv
index d3958ed0888b1feace153e45b057c976e986c882..e7f0067ec984784c3e762fa521b110f153c13823 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0050.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0050.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0051.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0051.csv
index 8611058fadcb38857b177e66f7e1897cb5b913af..9dfbcee65a0837faf80dc813da47ef308c6d4081 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0051.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0051.csv
@@ -1,112 +1,101 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0052.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0052.csv
index 8023646a44a8a5eb67ced2a1fd533834f6463f25..798db2a2320c1d2d18faeb1751e8dcbe12bc98ba 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0052.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0052.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0053.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0053.csv
index 28ed751e1ada926abb268a0c721b2f96c6624e88..3941e56cd0560b636eb585bd863a496a5f4581c9 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0053.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0053.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0054.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0054.csv
index 537344ddcde02e7c1a2a757e4ae7383b907f7828..69f42008721c3ab42620683b6cdeaae916f08b41 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0054.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0054.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0055.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0055.csv
index 747a5eaf8c9b080e064ccbe479369dfc74244e7b..4b8b0b698613ad1fe751980eca791af2b4464ac4 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0055.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0055.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0056.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0056.csv
index 20d39667af6b2dc2631daa4fcb1c9f9ab1e20f6b..9aed0cdf1d7abea529e407ddb3ed42039a6762b2 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0056.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0056.csv
@@ -1,127 +1,213 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0057.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0057.csv
index 53c019da60d7dfe0e888a7ba20e4501a7b83977d..fe9b32fc24a5e83fa9a614e34bf6d52d3d5e1576 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0057.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0057.csv
@@ -1,102 +1,202 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0058.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0058.csv
index 6383f4cb0c5f95334e7fc747cfa3730f2be819a4..4f30095e5e823d04af810f93a540cb93cf8944a7 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0058.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0058.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0059.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0059.csv
index 3319b5e646e818b027157a19edddcdbb23f608cf..22ac231b999c1a006a27484f39137a3895b6515e 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0059.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0059.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0060.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0060.csv
index 9ca8f8a60b1e049fe935e8945c04677e9621acbe..d54dab3b6e084f89635ef2d418517ae5fd9d9b61 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0060.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0060.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0061.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0061.csv
index df982b02fa8763e227bae1f9d32e193d6d55f61e..41dd191f09e3ebdff7adc92793cc85269a77e3c8 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0061.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0061.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0062.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0062.csv
index d69309fe39fb7ef62f6e34d9c8ea49ea0648193e..52178b08f5d7151db980205616191ed4f9131f6e 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0062.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0062.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0063.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0063.csv
index bdade93959f0c1275e065613d527978f7855e098..e4331b3bf2825e79bc442b0b55ffa20d405f9fe6 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0063.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0063.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0064.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0064.csv
index 444756eddc47a5764fff7b025593be3e8d3757f0..b92d656a68747405eeb9c5560a29fe1be38bb4e5 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0064.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0064.csv
@@ -1,78 +1,254 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0065.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0065.csv
index 7c434f24eae5fae3946170241917b437634ba676..0e1586b2024e2b29f45c300a5d723fced8f81e7f 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0065.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0065.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0066.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0066.csv
index adf105a555edd5796b18585da33bc556a905f522..c0fb0ef4ef32010ada2adf073e2adcc3be0ed9ec 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0066.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0066.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0067.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0067.csv
index 13cc3f5b051ba1c93bfb7e6bbf8e6831a2ecbb56..cff9e5fa1e8678a04fce7897354abeeed9b924f2 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0067.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0067.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0068.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0068.csv
index 33dae7982c6077ca12fbd995cfdc453e7f47bc95..48a15cb8aaa5217b384544fcaa41911194cdf3ae 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0068.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0068.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0069.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0069.csv
index 4edd4333fb33c0fbed80cd7fd49133c954d272db..f9548a2c154dfaab5f4e4535deadac3a39526f3a 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0069.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0069.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0070.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0070.csv
index 7d7816a2d600fc13c3f974451bc6a34fd74838dc..d3fd4fe123e5ff0d196bc7f17e0bca211d9d1104 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0070.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0070.csv
@@ -1,79 +1,198 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0071.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0071.csv
index ef7bb27122b279f4eb52924520e3eaed5efc76da..f2d4bc8154ffb0c9cec6c70d0d56c0611ba0d11a 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0071.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0071.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0072.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0072.csv
index 890efba2a3b95d54841ea49d24c692ec77590dd1..61a6fc1478d5f8f4ab04192a5a48303bdba6becc 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0072.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0072.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0073.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0073.csv
index 9ed1452dc8f25609fb7164ea53722a3720e6f0a6..005cebcf8d66f5ff226d78470b4b911fc6147c4d 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0073.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0073.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0074.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0074.csv
index 263c45d32ea9237a6861178c1b70e1b46e2909ac..739e125dc709bbfca9366cb20b039aa599c10f9b 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0074.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0074.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0075.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0075.csv
index 0f628ceb9e4b478610d8096d5db43fbb9c920240..6756bc7bc8d28f771545d5b3548778a55fde3b16 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0075.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0075.csv
@@ -1,72 +1,264 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0076.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0076.csv
index 5044ea47c96a3c906f85d6678a9ca400b4f8f430..2199d66e64258614f39f01d14fcb11699eb0e691 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0076.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0076.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0077.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0077.csv
index eb8e11c2455e89531bf9ae7c133f0258cb2b7755..3f27b52d8b683fff92f0b0eb3d1abc86703d78b9 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0077.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0077.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0078.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0078.csv
index 68092080c83f28306bfc927118db32c15212d4e9..c6486371e8869d22f5c3c22218dce1aee2d34962 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0078.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0078.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0079.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0079.csv
index 2844546c38323735ec7601ac63efaf3ccbb0579f..4cef320261818f97995567f9f90739f001777be4 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0079.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0079.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0080.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0080.csv
index f9287d791526cf92331af008096f23b36a57cced..5d9d8436c9c7584232a7610e74e018049af70900 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0080.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0080.csv
@@ -1,76 +1,136 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0081.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0081.csv
index 9fc8a51c05f38db005ae7e57516b38fe37c57a7e..83127af673f63567c386ec3fc8064482d22a0c74 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0081.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0081.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0082.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0082.csv
index 9fac3bdb773830dcdb6cebbdea5f7b0529f0fcf5..5f8fec5e997ebaf2ce1294b779fa8d2794c15b9c 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0082.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0082.csv
@@ -1,78 +1,240 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0083.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0083.csv
index 89a55a0a0aabde7f27c2c7ba30c925a15c7e4b9b..cccb292f5e54fad2bb74e3f8237f789cae9d8498 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0083.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0083.csv
@@ -1,77 +1,93 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0084.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0084.csv
index b88d8c3b3339dd4740fdfb1cc641a661e0889b2f..de82eace6ba63200135215ebcf89564d720eec91 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0084.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0084.csv
@@ -1,77 +1,198 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0085.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0085.csv
index 574b95d6ac9a1ada238f5cf840b55f7e4bb688c1..0ab985cf523cfb05e3b7710cfbb025bfc7ad329b 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0085.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0085.csv
@@ -1,79 +1,323 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0086.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0086.csv
index d3fc287861385572ce5ee8795605b493d81272c1..b6882ecdc6309349f9ca4653402451272f9f636c 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0086.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0086.csv
@@ -1,70 +1,87 @@
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0087.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0087.csv
index 8546c6112a4631d02261df04fa555d7b8937d17e..562799c0c439293451957b6294991fbd98310d2b 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0087.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0087.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0088.csv b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0088.csv
index 11e99a1af5048ba7837ede13c540151ebfdcca9d..2eb93edb526f1a12e51184d964ebb34e960ac16b 100644
--- a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0088.csv
+++ b/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0088.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0003.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0003.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7e78a2761a851fa9d51ae6237da8752f10406bc7
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0003.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0004.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0004.csv
new file mode 100644
index 0000000000000000000000000000000000000000..aa05c776c6359c71e8e466686635e6606bb192bd
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0004.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0005.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0005.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0dfd8d314715476f5ced7aa2762ada1553c17786
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0005.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0006.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0006.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5c09dbd1f3d8cd70e149a71a57dd9d8534e76af8
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0006.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0007.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0007.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e9f7dbda4adb7a7a440fd472e631a867b39d9351
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0007.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0008.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0008.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4f5c2649312fc739233f0d51ddb38980a3bf82d4
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0008.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0009.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0009.csv
new file mode 100644
index 0000000000000000000000000000000000000000..810389cb70b277366d9e6a0d6de54aa0ebdf8f65
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0009.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0010.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0010.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f18a61045566f031af73895af5a2932678daa5cc
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0010.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0011.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0011.csv
new file mode 100644
index 0000000000000000000000000000000000000000..93ca73360f27416e96b95d1105314d20f31802fe
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0011.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0012.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0012.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0c7b8b191dbadf2cae77d0355d79236e45ae3b4b
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0012.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0013.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0013.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0bce2f31a6db3dba3f1cc6a423b120938fc3d17e
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0013.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0014.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0014.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cb050df4e9f37dafa9ed219bd0d1bbbbc9eeaa80
--- /dev/null
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0015.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0015.csv
new file mode 100644
index 0000000000000000000000000000000000000000..63ad6366c9598a0a94c05cec26ed397b0e9330f9
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0015.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0016.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0016.csv
new file mode 100644
index 0000000000000000000000000000000000000000..619e5570c1698c6bac2f12f814012b7694e65a0c
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0016.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0017.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0017.csv
new file mode 100644
index 0000000000000000000000000000000000000000..11d4074cf7cbd5094c16909754e5af295c6970be
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0017.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0018.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0018.csv
new file mode 100644
index 0000000000000000000000000000000000000000..22335263e4c53f308362237e440b5cf11465f378
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0018.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0019.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0019.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7e0d16d9c885003d78c94d1f529ea8c0c88d50b5
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0019.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0020.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0020.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7319bed1d6e06a3721deaf63322e3841ec313911
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0020.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0021.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0021.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8925c77e1aac1234c2f349983b2eefc670b8c8c9
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0021.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0022.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0022.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d04e6516e50ff0d622214f2cbde6945e1d50a39a
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0022.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0023.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0023.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fa26869c243ab1e0ab1b7df5f2cc8acba8ac7eaf
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0023.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0024.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0024.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f1dfcb35d8010c5e91dfff9ea29055f6c8e33f1c
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0024.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0025.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0025.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ba800ec0cad12965bd498c23ee868480b7ce46af
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0025.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0026.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0026.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d96fea3c234bbcd25b65dc6548bc84e38bbf7690
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0026.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0027.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0027.csv
new file mode 100644
index 0000000000000000000000000000000000000000..439162836101aac386471853f2731585b7a77ce5
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0027.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0028.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0028.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d604928669cf2bac2f98f82314b721e65d435a34
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0028.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0029.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0029.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e49d565315fae5d4d020eaeccfc421650573ad05
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0029.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0030.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0030.csv
new file mode 100644
index 0000000000000000000000000000000000000000..551d6bdb8b0ec2e9513de9d9b0436dd39a149773
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0030.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0031.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0031.csv
new file mode 100644
index 0000000000000000000000000000000000000000..98b1e6e06856023f54025f32300a823abeb218e9
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0031.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0032.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0032.csv
new file mode 100644
index 0000000000000000000000000000000000000000..245f4932942dbfbc2135be5fe3e08b594a7fb413
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0032.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0033.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0033.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3b11db1fd7ddd16ed024bfbf22d70b1fd3b28a8b
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0033.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0034.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0034.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3c6e5098c6434d6c774d4f57da9dea1399b20d15
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0034.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0035.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0035.csv
new file mode 100644
index 0000000000000000000000000000000000000000..11923cd0b97a5ff0971a5e5e2c08216d155bb98c
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0035.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0036.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0036.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e6edcfcefa99e40a279a25266375e43c7deff0cf
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0036.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0037.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0037.csv
new file mode 100644
index 0000000000000000000000000000000000000000..11f4de7dc3c9d66ca4f555b65767ddbb50bb3654
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0037.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0038.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0038.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f98c70e0700b580012ef45d211cde4b4cfa19a3f
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0038.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0039.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0039.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1af747ec93e4244d8ee80fcca404e2e549ddc6a5
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0039.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0040.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0040.csv
new file mode 100644
index 0000000000000000000000000000000000000000..aebead2e6b44533bb5e1b0e51bb9784886162c14
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0040.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0041.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0041.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c297e1e8c6966eafe4a65554c73eca9427937f16
--- /dev/null
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0042.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0042.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0b2b52059f019d8d09bd2f40742f86cab3b7523b
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0042.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0043.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0043.csv
new file mode 100644
index 0000000000000000000000000000000000000000..79f2fb786fbe6aa90d0340d2cd838b0d67e7b2da
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0043.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0044.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0044.csv
new file mode 100644
index 0000000000000000000000000000000000000000..440f9a8689d267cef635da7149a061fc9b8d8063
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0044.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0045.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0045.csv
new file mode 100644
index 0000000000000000000000000000000000000000..71d25e72c77138eb51240687c162e789745de926
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0045.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0046.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0046.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e13193fac711e1320ab3ba47bad9d6cffb74aaa6
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0046.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0047.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0047.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bb6572ed5a4a100ee68fa9e8b80fa1e6b2df96cb
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0047.csv
@@ -0,0 +1,68 @@
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0048.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0048.csv
new file mode 100644
index 0000000000000000000000000000000000000000..594e01b5db10cf0afb2b73b6ab865ca944653760
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0048.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0049.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0049.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c5ddfec95f7c4cbf1aac4b76bc0d16903dd0b56d
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0049.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0050.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0050.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d3958ed0888b1feace153e45b057c976e986c882
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0050.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0051.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0051.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8611058fadcb38857b177e66f7e1897cb5b913af
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0051.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0052.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0052.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8023646a44a8a5eb67ced2a1fd533834f6463f25
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0052.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0053.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0053.csv
new file mode 100644
index 0000000000000000000000000000000000000000..28ed751e1ada926abb268a0c721b2f96c6624e88
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0053.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0054.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0054.csv
new file mode 100644
index 0000000000000000000000000000000000000000..537344ddcde02e7c1a2a757e4ae7383b907f7828
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0054.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0055.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0055.csv
new file mode 100644
index 0000000000000000000000000000000000000000..747a5eaf8c9b080e064ccbe479369dfc74244e7b
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0055.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0056.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0056.csv
new file mode 100644
index 0000000000000000000000000000000000000000..20d39667af6b2dc2631daa4fcb1c9f9ab1e20f6b
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0056.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0057.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0057.csv
new file mode 100644
index 0000000000000000000000000000000000000000..53c019da60d7dfe0e888a7ba20e4501a7b83977d
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0057.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0058.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0058.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6383f4cb0c5f95334e7fc747cfa3730f2be819a4
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0058.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0059.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0059.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3319b5e646e818b027157a19edddcdbb23f608cf
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0059.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0060.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0060.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9ca8f8a60b1e049fe935e8945c04677e9621acbe
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0060.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0061.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0061.csv
new file mode 100644
index 0000000000000000000000000000000000000000..df982b02fa8763e227bae1f9d32e193d6d55f61e
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0061.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0062.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0062.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d69309fe39fb7ef62f6e34d9c8ea49ea0648193e
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0062.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0063.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0063.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bdade93959f0c1275e065613d527978f7855e098
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0063.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0064.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0064.csv
new file mode 100644
index 0000000000000000000000000000000000000000..444756eddc47a5764fff7b025593be3e8d3757f0
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0064.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0065.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0065.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7c434f24eae5fae3946170241917b437634ba676
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0065.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0066.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0066.csv
new file mode 100644
index 0000000000000000000000000000000000000000..adf105a555edd5796b18585da33bc556a905f522
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0066.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0067.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0067.csv
new file mode 100644
index 0000000000000000000000000000000000000000..13cc3f5b051ba1c93bfb7e6bbf8e6831a2ecbb56
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0067.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0068.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0068.csv
new file mode 100644
index 0000000000000000000000000000000000000000..33dae7982c6077ca12fbd995cfdc453e7f47bc95
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0068.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0069.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0069.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4edd4333fb33c0fbed80cd7fd49133c954d272db
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0069.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0070.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0070.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7d7816a2d600fc13c3f974451bc6a34fd74838dc
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0070.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0071.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0071.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ef7bb27122b279f4eb52924520e3eaed5efc76da
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0071.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0072.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0072.csv
new file mode 100644
index 0000000000000000000000000000000000000000..890efba2a3b95d54841ea49d24c692ec77590dd1
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0072.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0073.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0073.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9ed1452dc8f25609fb7164ea53722a3720e6f0a6
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0073.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0074.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0074.csv
new file mode 100644
index 0000000000000000000000000000000000000000..263c45d32ea9237a6861178c1b70e1b46e2909ac
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0074.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0075.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0075.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0f628ceb9e4b478610d8096d5db43fbb9c920240
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0075.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0076.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0076.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5044ea47c96a3c906f85d6678a9ca400b4f8f430
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0076.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0077.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0077.csv
new file mode 100644
index 0000000000000000000000000000000000000000..eb8e11c2455e89531bf9ae7c133f0258cb2b7755
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0077.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0078.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0078.csv
new file mode 100644
index 0000000000000000000000000000000000000000..68092080c83f28306bfc927118db32c15212d4e9
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0078.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0079.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0079.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2844546c38323735ec7601ac63efaf3ccbb0579f
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0079.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0080.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0080.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f9287d791526cf92331af008096f23b36a57cced
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0080.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0081.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0081.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9fc8a51c05f38db005ae7e57516b38fe37c57a7e
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0081.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0082.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0082.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9fac3bdb773830dcdb6cebbdea5f7b0529f0fcf5
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0082.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0083.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0083.csv
new file mode 100644
index 0000000000000000000000000000000000000000..89a55a0a0aabde7f27c2c7ba30c925a15c7e4b9b
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0083.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0084.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0084.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b88d8c3b3339dd4740fdfb1cc641a661e0889b2f
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0084.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0085.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0085.csv
new file mode 100644
index 0000000000000000000000000000000000000000..574b95d6ac9a1ada238f5cf840b55f7e4bb688c1
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0085.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0086.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0086.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d3fc287861385572ce5ee8795605b493d81272c1
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0086.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0087.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0087.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8546c6112a4631d02261df04fa555d7b8937d17e
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0087.csv
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diff --git a/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0088.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0088.csv
new file mode 100644
index 0000000000000000000000000000000000000000..11e99a1af5048ba7837ede13c540151ebfdcca9d
--- /dev/null
+++ b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0088.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0089.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0089.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0089.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0089.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0090.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0090.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0090.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0090.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0091.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0091.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0091.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0092.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0092.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0092.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0093.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0093.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0093.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0093.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0094.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0094.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0094.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0094.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0095.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0095.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0095.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0096.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0096.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0096.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0097.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0097.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0097.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0098.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0098.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0098.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0099.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0099.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0099.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0099.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0100.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0100.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0100.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0100.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0101.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0101.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0101.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0101.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0102.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0102.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0102.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0102.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0103.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0103.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0103.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0103.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0104.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0104.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0104.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0104.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0105.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0105.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0105.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0105.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0106.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0106.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0106.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0106.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0107.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0107.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0107.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0108.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0108.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0108.csv
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diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0109.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0109.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0109.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0109.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0110.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0110.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0110.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0110.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0111.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0111.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0111.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0111.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0112.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0112.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0112.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0112.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0113.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0113.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0113.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0113.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0114.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0114.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0114.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0114.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0115.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0115.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0115.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0115.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0116.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0116.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0116.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0116.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0117.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0117.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0117.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0117.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0118.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0118.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0118.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0118.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0119.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0119.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0119.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0119.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0120.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0120.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0120.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0120.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0121.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0121.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0121.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0121.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0122.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0122.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0122.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0122.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0123.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0123.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0123.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0123.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0124.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0124.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0124.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0124.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0125.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0125.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0125.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0125.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0126.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0126.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0126.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0126.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0127.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0127.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0127.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0127.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0128.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0128.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0128.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0128.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0129.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0129.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0129.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0129.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0130.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0130.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0130.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0130.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0131.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0131.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0131.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0131.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0132.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0132.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0132.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0132.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0133.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0133.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0133.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0133.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0134.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0134.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0134.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0134.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0135.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0135.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0135.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0135.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0136.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0136.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0136.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0136.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0137.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0137.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0137.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0137.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0138.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0138.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0138.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0138.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0139.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0139.csv
similarity index 100%
rename from src/main/java/vslam/KeyFramePoints/KeyFramePoints_0139.csv
rename to src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0139.csv
diff --git a/src/main/java/vslam/KeyFramePoints/KeyFramePoints_0140.csv b/src/main/java/vslam/KeyFramePoints_Mono/KeyFramePoints_0140.csv
similarity index 100%
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diff --git a/src/main/java/vslam/KeyFrames/KeyFrame_0143.png b/src/main/java/vslam/KeyFrames_Mono/KeyFrame_0143.png
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diff --git a/src/main/java/vslam/KeyFrames/KeyFrame_0153.png b/src/main/java/vslam/KeyFrames_Mono/KeyFrame_0153.png
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diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/VisualSLAMWithAnRGBDCameraExample.mlx b/src/main/java/vslam/Mathworks_VSLAM_RGBD/VisualSLAMWithAnRGBDCameraExample.mlx
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diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/bagOfFeaturesDataSLAM.mat b/src/main/java/vslam/Mathworks_VSLAM_RGBD/bagOfFeaturesDataSLAM.mat
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diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperAddLoopConnectionsStereo.m b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperAddLoopConnectionsStereo.m
new file mode 100644
index 0000000000000000000000000000000000000000..5ddcc506b3caa8b678b41692fdd27289826c70d7
--- /dev/null
+++ b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperAddLoopConnectionsStereo.m
@@ -0,0 +1,81 @@
+function [isLoopClosed, mapPoints, vSetKeyFrames] = helperAddLoopConnectionsStereo(...
+    mapPoints, vSetKeyFrames, loopCandidates, currKeyFrameId, currFeatures, ...
+    currPoints, loopEdgeNumMatches, varargin)
+%helperAddLoopConnectionsStereo add connections between the current key frame and
+%   the valid loop candidate key frames. A loop candidate is valid if it has
+%   enough covisible map points with the current key frame.
+
+%   This is an example helper function that is subject to change or removal
+%   in future releases.
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+if nargin > 7
+    maxDistance = varargin{1};
+else
+    maxDistance = 4;
+end
+
+loopClosureEdge = [];
+
+numCandidates   = size(loopCandidates,2);
+[index3d1, index2d1] = findWorldPointsInView(mapPoints, currKeyFrameId);
+validFeatures1  = currFeatures.Features(index2d1, :);
+validPoints1    = currPoints(index2d1, :);
+
+for k = 1 : numCandidates
+    [index3d2, index2d2] = findWorldPointsInView(mapPoints, loopCandidates(k));
+    allFeatures2   = vSetKeyFrames.Views.Features{loopCandidates(k)};
+    allPoints2     = vSetKeyFrames.Views.Points{loopCandidates(k)};
+    validFeatures2 = allFeatures2(index2d2, :);
+    validPoints2   = allPoints2(index2d2, :);
+    
+    indexPairs = matchFeatures(binaryFeatures(validFeatures1), binaryFeatures(validFeatures2), ...
+        'Unique', true, 'MaxRatio', 0.9, 'MatchThreshold', 40);
+    
+    % Orientation consistency check
+    orientation1 = validPoints1.Orientation(indexPairs(:,1));
+    orientation2 = validPoints2.Orientation(indexPairs(:,2));
+    [N, ~, bin] = histcounts(abs(orientation1 - orientation2), 0:pi/30:2*pi);
+    [~, ia] = maxk(N, 3); % Select the top 3 bins
+    isConsistent = ismember(bin, ia);
+
+    indexPairs = indexPairs(isConsistent, :);
+
+    % Check if all the candidate key frames have strong connection with the
+    % current keyframe
+    if size(indexPairs, 1) < loopEdgeNumMatches
+        continue
+    end
+    
+    % Estimate the relative pose of the current key frame with respect to the
+    % loop candidate keyframe with the highest similarity score
+    
+    worldPoints1 = mapPoints.WorldPoints(index3d1(indexPairs(:, 1)), :);
+    worldPoints2 = mapPoints.WorldPoints(index3d2(indexPairs(:, 2)), :);
+
+    tform1 = pose2extr(vSetKeyFrames.Views.AbsolutePose(end));
+    tform2 = pose2extr(vSetKeyFrames.Views.AbsolutePose(loopCandidates(k)));
+
+    worldPoints1InCamera1 = transformPointsForward(tform1, worldPoints1); 
+    worldPoints2InCamera2 = transformPointsForward(tform2, worldPoints2); 
+    
+    w = warning('off','all');
+    [tform, inlierIndex] = estgeotform3d(worldPoints1InCamera1, ...
+        worldPoints2InCamera2, 'rigid', 'MaxNumTrials', 1e4, 'MaxDistance', maxDistance);
+    warning(w);
+
+    % Add connection between the current key frame and the loop key frame
+    matches = uint32([index2d2(indexPairs(inlierIndex, 2)), index2d1(indexPairs(inlierIndex, 1))]);
+    vSetKeyFrames = addConnection(vSetKeyFrames, loopCandidates(k), currKeyFrameId, tform, 'Matches', matches);
+    disp(['Loop edge added between keyframe: ', num2str(loopCandidates(k)), ' and ', num2str(currKeyFrameId)]);
+    
+    % Fuse co-visible map points
+    matchedIndex3d1 = index3d1(indexPairs(inlierIndex, 1));
+    matchedIndex3d2 = index3d2(indexPairs(inlierIndex, 2));
+    mapPoints = updateWorldPoints(mapPoints, matchedIndex3d1, mapPoints.WorldPoints(matchedIndex3d2, :));
+    
+    loopClosureEdge = [loopClosureEdge; loopCandidates(k), currKeyFrameId];
+end
+isLoopClosed = ~isempty(loopClosureEdge);
+end
\ No newline at end of file
diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperAddNewKeyFrame.m b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperAddNewKeyFrame.m
new file mode 100644
index 0000000000000000000000000000000000000000..8171da4598e2f5e654d532de5f2eafe794b88a54
--- /dev/null
+++ b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperAddNewKeyFrame.m
@@ -0,0 +1,54 @@
+function [mapPoints, vSetKeyFrames] = helperAddNewKeyFrame(mapPoints, vSetKeyFrames,...
+    cameraPose, currFeatures, currPoints, mapPointsIndices, featureIndices, keyFramesIndices)
+%helperAddNewKeyFrame add key frames to the key frame set
+%
+%   This is an example helper function that is subject to change or removal
+%   in future releases.
+
+%   Copyright 2019-2023 The MathWorks, Inc.
+%#codegen
+
+viewId = vSetKeyFrames.Views.ViewId(end)+1;
+
+vSetKeyFrames = addView(vSetKeyFrames, viewId, cameraPose,...
+    'Features', currFeatures.Features, ...
+    'Points', currPoints);
+
+viewsAbsPoses = vSetKeyFrames.Views.AbsolutePose;
+
+for i = 1:numel(keyFramesIndices)
+    localKeyFrameId = keyFramesIndices(i);
+    if isSimMode()
+        [index3d, index2d] = findWorldPointsInView(mapPoints, localKeyFrameId);
+    else
+        [index3dCg, index2dCg] = findWorldPointsInView(mapPoints, localKeyFrameId);
+        index3d = index3dCg{1};
+        index2d = index2dCg{1};
+    end
+    [~, ia, ib] = intersect(index3d, mapPointsIndices, 'stable');
+
+    prePose   = viewsAbsPoses(localKeyFrameId);
+    relPose = rigidtform3d(prePose.R' * cameraPose.R, ...
+        (cameraPose.Translation-prePose.Translation)*prePose.R);
+
+    if numel(ia) > 5
+        if isSimMode()
+            vSetKeyFrames = addConnection(vSetKeyFrames, localKeyFrameId, viewId, relPose, ...
+                'Matches', [index2d(ia),featureIndices(ib)]);
+        else
+            coder.varsize('matches', [inf 2], [1, 0]);
+            fIndices = featureIndices(ib(:));
+            matches = [index2d(ia), fIndices];
+            vSetKeyFrames = addConnection(vSetKeyFrames, localKeyFrameId, viewId, relPose, ...
+                'Matches', matches);
+        end
+    end
+end
+
+mapPoints = addCorrespondences(mapPoints, viewId, mapPointsIndices, ...
+    featureIndices);
+end
+
+function tf = isSimMode()
+    tf = isempty(coder.target);
+end
\ No newline at end of file
diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperCheckLoopClosure.m b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperCheckLoopClosure.m
new file mode 100644
index 0000000000000000000000000000000000000000..7cff3e85c2f308126c160e6d73176923a5b38914
--- /dev/null
+++ b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperCheckLoopClosure.m
@@ -0,0 +1,58 @@
+function [isDetected, loopKeyFrameIds] = helperCheckLoopClosure(vSetKeyFrames, ...
+    currKeyframeId, imageDatabase, currImg, loopEdgeNumMatches)
+%helperCheckLoopClosure detect loop candidates key frames by retrieving
+%   visually similar images from the feature database.
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2019-2023 The MathWorks, Inc.
+%#codegen
+
+% Retrieve all the visually similar key frames
+[candidateViewIds, similarityscores] = retrieveImages(currImg, imageDatabase);
+
+% Compute similarity between the current key frame and its strongly-connected 
+% key frames. The minimum similarity score is used as a baseline to find 
+% loop candidate key frames, which are visually similar to but not connected 
+% to the current key frame
+covisViews          = connectedViews(vSetKeyFrames, currKeyframeId);
+covisViewsIds       = covisViews.ViewId;
+strongCovisViews    = connectedViews(vSetKeyFrames, currKeyframeId, 'MinNumMatches', loopEdgeNumMatches);
+strongCovisViewIds  = strongCovisViews.ViewId;
+
+% Retrieve the top 10 similar connected key frames
+[~,~,scores] = evaluateImageRetrieval(currImg, imageDatabase, strongCovisViewIds, 'NumResults', 10);
+minScore     = min(scores);
+
+[loopKeyFrameIds,ia] = setdiff(candidateViewIds, covisViewsIds, 'stable');
+
+% Scores of non-connected key frames
+candidateScores  = similarityscores(ia); % Descending
+
+if ~isempty(ia)
+    bestScore       = candidateScores(1);
+    
+    % Score must be higher than the 75% of the best score 
+    isValid         = candidateScores > max(bestScore*0.75, minScore);
+    
+    loopKeyFrameIds = loopKeyFrameIds(isValid);
+else
+    loopKeyFrameIds = zeros(coder.ignoreConst(0), coder.ignoreConst(0), class(loopKeyFrameIds));
+end
+
+% Loop candidates need to be consecutively detected
+minNumCandidates = 3; % At least 3 candidates are found
+if size(loopKeyFrameIds,1) >= minNumCandidates
+    groups = nchoosek(loopKeyFrameIds, minNumCandidates);
+    consecutiveGroups = groups(max(groups,[],2) - min(groups,[],2) < 4, :);
+    if ~isempty(consecutiveGroups) % Consecutive candidates are found
+        loopKeyFrameIds = consecutiveGroups(1,:);
+        isDetected = true;
+    else
+        isDetected = false;
+    end
+else
+    isDetected = false;
+end
+end
\ No newline at end of file
diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperCreateNewMapPointsStereo.m b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperCreateNewMapPointsStereo.m
new file mode 100644
index 0000000000000000000000000000000000000000..c66582c070cc9b01fcf8964b53f70b124810d02d
--- /dev/null
+++ b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperCreateNewMapPointsStereo.m
@@ -0,0 +1,257 @@
+function [mapPoints, vSetKeyFrames, recentPointIdx, stereoMapPointsIndices] = helperCreateNewMapPointsStereo(...
+    mapPoints, vSetKeyFrames, currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax, ...
+    unmatchedFeatureIdx, stereoMapPointsIndices)
+%helperCreateNewMapPointsStereo creates new map points by triangulating matched
+%   feature points in the current key frame and the connected key frames.
+%
+%   This is an example helper function that is subject to change or removal
+%   in future releases.
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+% Get connected key frames
+KcViews  = connectedViews(vSetKeyFrames, currKeyFrameId, minNumMatches);
+KcIDs    = KcViews.ViewId;
+
+% Retreive data of the current key frame
+currPose        = vSetKeyFrames.Views.AbsolutePose(currKeyFrameId);
+currFeatures    = vSetKeyFrames.Views.Features{currKeyFrameId};
+currPoints      = vSetKeyFrames.Views.Points{currKeyFrameId};
+currLocations   = currPoints.Location;
+currScales      = currPoints.Scale;
+
+% Camera projection matrix
+currCamMatrix   = cameraProjection(intrinsics, pose2extr(currPose));
+
+recentPointIdx  = [];
+
+for i = numel(KcIDs):-1:1
+    
+    kfPose      = vSetKeyFrames.Views.AbsolutePose(KcIDs(i));
+    [~, kfIndex2d] = findWorldPointsInView(mapPoints, KcIDs(i));
+        kfCamMatrix = cameraProjection(intrinsics, pose2extr(kfPose));
+    
+    % Skip the key frame is the change of view is small
+    isViewClose = norm(kfPose.Translation - currPose.Translation) < 0.2; %baseline
+    if isViewClose
+        continue
+    end
+    
+    % Retrieve data of the connected key frame
+    kfFeatures  = vSetKeyFrames.Views.Features{KcIDs(i)};
+    kfPoints    = vSetKeyFrames.Views.Points{KcIDs(i)};
+    kfLocations = kfPoints.Location;
+    kfScales    = kfPoints.Scale;
+    
+    % currIndex2d changes in each iteration as new map points are created
+    [~, currIndex2d] = findWorldPointsInView(mapPoints, currKeyFrameId);
+    
+    % Only use unmatched feature points
+    uIndices1   = setdiff(uint32(1:size(kfFeatures,1))',  kfIndex2d);
+    uIndices2   = [setdiff(uint32(1:size(currFeatures,1))', currIndex2d); unmatchedFeatureIdx];
+    
+    uFeatures1  = kfFeatures(uIndices1, :);
+    uFeatures2  = currFeatures(uIndices2, :);
+    
+    uLocations1 = kfLocations(uIndices1, :);
+    uLocations2 = currLocations(uIndices2, :);
+    
+    uScales1    = kfScales(uIndices1);
+    uScales2    = currScales(uIndices2);
+    
+    indexPairs  = matchFeatures(binaryFeatures(uFeatures1), binaryFeatures(uFeatures2),...
+        'Unique', true, 'MaxRatio', 0.7, 'MatchThreshold', 40);
+    
+    if isempty(indexPairs)
+        continue
+    end
+    
+    % Created from stereo
+    [~, ia, ib] = intersect(unmatchedFeatureIdx, uIndices2(indexPairs(:, 2)));
+    
+    isNewPointStereo = ~isempty(ia);
+    
+    if isNewPointStereo
+        sIndices1 = uIndices1(indexPairs(ib, 1));
+        sIndices2 = unmatchedFeatureIdx(ia);
+        
+        % Update the indices
+        unmatchedFeatureIdx = setdiff(unmatchedFeatureIdx, sIndices2);
+        
+        % Filtering by view direction and reprojection error
+        xyzPoints = mapPoints.WorldPoints(stereoMapPointsIndices(ia), :);
+        
+        % Compute reprojection errors
+        [points1proj, isInFrontOfCam1] = projectPoints(xyzPoints, kfCamMatrix);
+        [points2proj, isInFrontOfCam2] = projectPoints(xyzPoints, currCamMatrix);
+        points1 = uLocations1(indexPairs(ib, 1), :)';
+        points2 = uLocations2(indexPairs(ib, 2), :)';
+        errors1 = hypot(points1(1,:)-points1proj(1,:), ...
+            points1(2,:) - points1proj(2,:));
+        errors2 = hypot(points2(1,:)-points2proj(1,:), ...
+            points2(2,:) - points2proj(2,:));
+        
+        reprojectionErrors = mean([errors1; errors2])';
+        
+        isValid = checkEpipolarConstraint(intrinsics, currPose, kfPose, points1', points2', indexPairs(ib, :), uScales2);
+        
+        validIdx = isInFrontOfCam1 & isInFrontOfCam2 & isValid;
+        
+        inlier = filterTriangulatedMapPoints(xyzPoints, kfPose, currPose, ...
+            uScales1(indexPairs(ib, 1)), uScales2(indexPairs(ib, 2)), ...
+            reprojectionErrors, scaleFactor, validIdx);
+        
+        if any(inlier)
+            mapPoints = addCorrespondences(mapPoints, KcIDs(i), stereoMapPointsIndices(ia(inlier)), sIndices1(inlier));
+            recentPointIdx = union(recentPointIdx, stereoMapPointsIndices(ia(inlier)));
+            recentPointIdx = recentPointIdx(:);
+        end
+        
+        % Created from triangulation
+        isNotPicked = true(size(indexPairs, 1), 1);
+        isNotPicked(ib(inlier)) = false;
+        indexPairs = indexPairs(isNotPicked, :);
+    end
+    
+    if isempty(indexPairs)
+        continue
+    end
+    
+    % Need to determine which way the new world points are created
+    matchedPoints1 = uLocations1(indexPairs(:,1), :);
+    matchedPoints2 = uLocations2(indexPairs(:,2), :);
+    
+    % Check epipolar constraint
+    isValid = checkEpipolarConstraint(intrinsics, currPose, kfPose, matchedPoints1, matchedPoints2, indexPairs, uScales2);
+    
+    indexPairs = indexPairs(isValid, :);
+    matchedPoints1 = matchedPoints1(isValid, :);
+    matchedPoints2 = matchedPoints2(isValid, :);
+    
+    % Parallax check
+    isLarge = isLargeParalalx(matchedPoints1, matchedPoints2, kfPose, ...
+        currPose, intrinsics, minParallax);
+    
+    matchedPoints1  = matchedPoints1(isLarge, :);
+    matchedPoints2  = matchedPoints2(isLarge, :);
+    indexPairs      = indexPairs(isLarge, :);
+    
+    % Triangulate two views to create new world points
+    [xyzPoints, reprojectionErrors, validIdx] = triangulate(matchedPoints1, ...
+        matchedPoints2, kfCamMatrix, currCamMatrix);
+    
+    % Filtering by view direction and reprojection error
+    inlier = filterTriangulatedMapPoints(xyzPoints, kfPose, currPose, ...
+        uScales1(indexPairs(:,1)), uScales2(indexPairs(:,2)), ...
+        reprojectionErrors, scaleFactor, validIdx);
+    
+    % Add new map points and update connections
+    addedMatches = [];
+    if any(inlier)
+        xyzPoints   = xyzPoints(inlier,:);
+        indexPairs  = indexPairs(inlier, :);
+        
+        mIndices1   = uIndices1(indexPairs(:, 1));
+        mIndices2   = uIndices2(indexPairs(:, 2));
+        
+        [mapPoints, indices] = addWorldPoints(mapPoints, xyzPoints);
+        recentPointIdx       = [recentPointIdx; indices]; %#ok<AGROW>
+        
+        % Add new observations
+        mapPoints  = addCorrespondences(mapPoints, KcIDs(i),indices, mIndices1);
+        mapPoints  = addCorrespondences(mapPoints, currKeyFrameId, indices, mIndices2);
+        
+        addedMatches = [mIndices1, mIndices2]; % Triangulation
+    end
+    
+    if isNewPointStereo
+        addedMatches = [sIndices1, sIndices2; addedMatches];
+    end   
+    
+    % Update connections with new feature matches
+    [~,ia]     = intersect(vSetKeyFrames.Connections{:,1:2}, ...
+        [KcIDs(i), currKeyFrameId], 'row', 'stable');
+    oldMatches = vSetKeyFrames.Connections.Matches{ia};
+    newMatches = [oldMatches; addedMatches];
+    vSetKeyFrames  = updateConnection(vSetKeyFrames, KcIDs(i), currKeyFrameId, ...
+        'Matches', newMatches);
+    
+end
+
+stereoMapPointsIndices = setdiff(stereoMapPointsIndices, recentPointIdx);
+end
+
+function F = computeF(intrinsics, pose1, pose2)
+R1 = pose1.R;
+t1 = pose1.Translation';
+
+R2 = pose2.R;
+t2 = pose2.Translation';
+
+R12 = R1'*R2;
+t12 = R1'*(t2-t1);
+
+% Skew symmetric matrix
+t12x = [0, -t12(3), t12(2)
+    t12(3), 0, -t12(1)
+    -t12(2) t12(1), 0];
+
+F = intrinsics.K'\ t12x * R12 / intrinsics.K;
+end
+
+function inlier = filterTriangulatedMapPoints(xyzPoints, pose1, pose2, ...
+    scales1, scales2, reprojectionErrors, scaleFactor, isInFront)
+
+camToPoints1= xyzPoints - pose1.Translation;
+camToPoints2= xyzPoints - pose2.Translation;
+
+% Check scale consistency and reprojection errors
+distances1  = vecnorm(camToPoints1, 2, 2);
+distances2  = vecnorm(camToPoints2, 2, 2);
+ratioDist   = distances1./distances2;
+ratioScale  = scales2./scales1;
+
+ratioFactor = 1.5 * scaleFactor;
+
+isInScale   = (ratioDist./ratioScale < ratioFactor  |  ...
+    ratioScale./ratioDist < ratioFactor);
+
+maxError    = sqrt(6);
+isSmallError= reprojectionErrors < maxError*min(scales1, scales2);
+inlier      = isInScale & isSmallError & isInFront;
+end
+
+function isLarge = isLargeParalalx(points1, points2, pose1, pose2, intrinsics, minParallax)
+
+% Parallax check
+K = intrinsics.IntrinsicMatrix;
+ray1 = [points1, ones(size(points1(:,1)))]/K *pose1.Rotation;
+ray2 = [points2, ones(size(points1(:,2)))]/K *pose2.Rotation;
+
+cosParallax = sum(ray1 .* ray2, 2) ./(vecnorm(ray1, 2, 2) .* vecnorm(ray2, 2, 2));
+isLarge     = cosParallax < cosd(minParallax) & cosParallax > 0;
+end
+
+%--------------------------------------------------------------------------
+function [points2d, isInFrontOfCamera] = projectPoints(points3d, P)
+points3dHomog = [points3d, ones(size(points3d, 1), 1, 'like', points3d)]';
+points2dHomog = P * points3dHomog;
+isInFrontOfCamera = points2dHomog(3, :)' > 0;
+points2d = bsxfun(@rdivide, points2dHomog(1:2, :), points2dHomog(3, :));
+end
+
+function isValid = checkEpipolarConstraint(intrinsics, currPose, kfPose, matchedPoints1, matchedPoints2, indexPairs, uScales2)
+% Epipole in the current key frame
+epiPole = world2img(kfPose.Translation, pose2extr(currPose), intrinsics);
+distToEpipole = vecnorm(matchedPoints2 - epiPole, 2, 2);
+
+% Compute fundamental matrix
+F = computeF(intrinsics, kfPose, currPose);
+
+% Epipolar line in the second image
+epiLine = epipolarLine(F, matchedPoints2);
+distToLine = abs(sum(epiLine.* [matchedPoints1, ones(size(matchedPoints1,1), 1)], 2))./...
+    sqrt(sum(epiLine(:,1:2).^2, 2));
+isValid = distToLine < 2*uScales2(indexPairs(:,2)) & ...
+    distToEpipole > 10*uScales2(indexPairs(:,2));
+end
\ No newline at end of file
diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperLocalBundleAdjustmentStereo.m b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperLocalBundleAdjustmentStereo.m
new file mode 100644
index 0000000000000000000000000000000000000000..1272b7951bbf8e6d80da44cd4b1a590038d46e4c
--- /dev/null
+++ b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperLocalBundleAdjustmentStereo.m
@@ -0,0 +1,49 @@
+function [mapPoints, vSetKeyFrames, newPointIdx, stereoMapPointsIndices] = helperLocalBundleAdjustmentStereo(mapPoints, ...
+    vSetKeyFrames, currKeyFrameId, intrinsics, newPointIdx, stereoMapPointsIndices)
+%helperLocalBundleAdjustmentStereo refine the pose of the current key frame and 
+%   the map of the surrrounding scene.
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2020-2022 The MathWorks, Inc.
+
+if currKeyFrameId > 2
+
+    [refinedViews, dist] = connectedViews(vSetKeyFrames, currKeyFrameId, MaxDistance=2);
+    refinedKeyFrameIds = refinedViews.ViewId;
+
+    % Always fix the first two key frames
+    fixedViewIds = refinedKeyFrameIds(dist==2);
+    fixedViewIds = fixedViewIds(1:min(10, numel(fixedViewIds)));
+
+    % Always fix the first two key frames
+    fixedViewIds = [fixedViewIds; intersect(refinedKeyFrameIds, [1 2])];
+
+    refinedKeyFrameIds = [refinedKeyFrameIds; currKeyFrameId];
+
+else
+    refinedKeyFrameIds = [1 2];
+    fixedViewIds = 1;
+end
+
+% Refine local key frames and map points
+[mapPoints, vSetKeyFrames, mapPointIdx, reprojectionErrors] = bundleAdjustment(...
+    mapPoints, vSetKeyFrames, refinedKeyFrameIds, intrinsics, 'FixedViewIDs', fixedViewIds, ...
+    'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,...
+    'RelativeTolerance', 1e-16, 'Solver', 'preconditioned-conjugate-gradient', ...
+    'MaxIteration', 10);
+
+maxError    = 6;
+isInlier    = reprojectionErrors < maxError;
+outlierIdx  = mapPointIdx(~isInlier);
+newPointIdx = setdiff(newPointIdx, outlierIdx);
+
+% Update map points and key frames
+if ~isempty(outlierIdx)
+    mapPoints = removeWorldPoints(mapPoints, outlierIdx);
+end
+
+newPointIdx = newPointIdx - arrayfun(@(x) nnz(x>outlierIdx), newPointIdx);
+stereoMapPointsIndices = stereoMapPointsIndices - arrayfun(@(x) nnz(x>outlierIdx), stereoMapPointsIndices);
+end
\ No newline at end of file
diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperORBFeatureExtractorFunction.m b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperORBFeatureExtractorFunction.m
new file mode 100644
index 0000000000000000000000000000000000000000..d8c77bf675b0e62057d8b72b15581914ba951f22
--- /dev/null
+++ b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperORBFeatureExtractorFunction.m
@@ -0,0 +1,25 @@
+function [features, featureMetrics]= helperORBFeatureExtractorFunction(I)
+% helperORBFeatureExtractorFunction Implements the ORB feature extraction 
+% used in bagOfFeatures.
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2021 The MathWorks, Inc.
+
+numPoints   = 1000;
+
+% Detect ORB features
+Igray  = im2gray(I);
+
+points = detectORBFeatures(Igray, 'ScaleFactor', 1.2, 'NumLevels', 8);
+
+% Select a subset of features, uniformly distributed throughout the image
+points = selectUniform(points, numPoints, size(Igray, 1:2));
+
+% Extract features
+features = extractFeatures(Igray, points);
+
+% Compute the Feature Metric. Use the variance of features as the metric
+featureMetrics = var(single(features.Features),[],2);
+
diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperTrackLastKeyFrame.m b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperTrackLastKeyFrame.m
new file mode 100644
index 0000000000000000000000000000000000000000..467ff8188bc13a55f385e8062267d67f5d77ff54
--- /dev/null
+++ b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperTrackLastKeyFrame.m
@@ -0,0 +1,106 @@
+%helperTrackLastKeyFrame Estimate the camera pose by tracking the last key frame
+%   [currPose, mapPointIdx, featureIdx] = helperTrackLastKeyFrameStereo(mapPoints, 
+%   views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor) estimates
+%   the camera pose of the current frame by matching features with the
+%   previous key frame.
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+%
+%   Inputs
+%   ------
+%   mapPoints         - A helperMapPoints objects storing map points
+%   views             - View attributes of key frames
+%   currFeatures      - Features in the current frame 
+%   currPoints        - Feature points in the current frame                 
+%   lastKeyFrameId    - ViewId of the last key frame 
+%   intrinsics        - Camera intrinsics 
+%   scaleFactor       - scale factor of features
+%   
+%   Outputs
+%   -------
+%   currPose          - Estimated camera pose of the current frame
+%   mapPointIdx       - Indices of map points observed in the current frame
+%   featureIdx        - Indices of features corresponding to mapPointIdx
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+function [currPose, mapPointIdx, featureIdx] = helperTrackLastKeyFrame(...
+    mapPoints, views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor)
+
+% Match features from the previous key frame with known world locations
+[index3d, index2d]    = findWorldPointsInView(mapPoints, lastKeyFrameId);
+lastKeyFrameFeatures  = views.Features{lastKeyFrameId}(index2d,:);
+lastKeyFramePoints    = views.Points{lastKeyFrameId}(index2d);
+
+indexPairs  = matchFeatures(currFeatures, binaryFeatures(lastKeyFrameFeatures),...
+    'Unique', true, 'MaxRatio', 0.9, 'MatchThreshold', 40);
+
+% Estimate the camera pose
+matchedImagePoints = currPoints.Location(indexPairs(:,1),:);
+matchedWorldPoints = mapPoints.WorldPoints(index3d(indexPairs(:,2)), :);
+
+matchedImagePoints = cast(matchedImagePoints, 'like', matchedWorldPoints);
+[currPose, inlier, status] = estworldpose(...
+    matchedImagePoints, matchedWorldPoints, intrinsics, ...
+    'Confidence', 95, 'MaxReprojectionError', 3, 'MaxNumTrials', 1e4);
+
+if status
+    currPose=[];
+    mapPointIdx=[];
+    featureIdx=[];
+    return
+end
+
+% Refine camera pose only
+currPose = bundleAdjustmentMotion(matchedWorldPoints(inlier,:), ...
+    matchedImagePoints(inlier,:), currPose, intrinsics, ...
+    'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,...
+    'RelativeTolerance', 1e-15, 'MaxIteration', 20);
+
+% Search for more matches with the map points in the previous key frame
+xyzPoints = mapPoints.WorldPoints(index3d,:);
+
+[projectedPoints, isInImage] = world2img(xyzPoints, pose2extr(currPose), intrinsics);
+projectedPoints = projectedPoints(isInImage, :);
+
+minScales    = max(1, lastKeyFramePoints.Scale(isInImage)/scaleFactor);
+maxScales    = lastKeyFramePoints.Scale(isInImage)*scaleFactor;
+r            = 4;
+searchRadius = r*lastKeyFramePoints.Scale(isInImage);
+
+indexPairs   = matchFeaturesInRadius(binaryFeatures(lastKeyFrameFeatures(isInImage,:)), ...
+    binaryFeatures(currFeatures.Features), currPoints, projectedPoints, searchRadius, ...
+    'MatchThreshold', 40, 'MaxRatio', 0.8, 'Unique', true);
+
+if size(indexPairs, 1) < 20
+    indexPairs   = matchFeaturesInRadius(binaryFeatures(lastKeyFrameFeatures(isInImage,:)), ...
+        binaryFeatures(currFeatures.Features), currPoints, projectedPoints, 2*searchRadius, ...
+        'MatchThreshold', 40, 'MaxRatio', 1, 'Unique', true);
+end
+
+if size(indexPairs, 1) < 10
+    currPose=[];
+    mapPointIdx=[];
+    featureIdx=[];
+    return
+end
+
+% Filter by scales
+isGoodScale = currPoints.Scale(indexPairs(:, 2)) >= minScales(indexPairs(:, 1)) & ...
+    currPoints.Scale(indexPairs(:, 2)) <= maxScales(indexPairs(:, 1));
+indexPairs  = indexPairs(isGoodScale, :);
+
+% Obtain the index of matched map points and features
+tempIdx            = find(isInImage); % Convert to linear index
+mapPointIdx        = index3d(tempIdx(indexPairs(:,1)));
+featureIdx         = indexPairs(:,2);
+
+% Refine the camera pose again
+matchedWorldPoints = mapPoints.WorldPoints(mapPointIdx, :);
+matchedImagePoints = currPoints.Location(featureIdx, :);
+
+currPose = bundleAdjustmentMotion(matchedWorldPoints, matchedImagePoints, ...
+    currPose, intrinsics, 'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,...
+    'RelativeTolerance', 1e-15, 'MaxIteration', 20);
+end
\ No newline at end of file
diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperTrackLocalMap.m b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperTrackLocalMap.m
new file mode 100644
index 0000000000000000000000000000000000000000..d64da7a28ae032e7fd6db8a0e0b689a2c90d06a6
--- /dev/null
+++ b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperTrackLocalMap.m
@@ -0,0 +1,221 @@
+function [localKeyFrameIds, currPose, mapPointIdx, featureIdx, isKeyFrame] = ...
+    helperTrackLocalMap(mapPoints, vSetKeyFrames, mapPointIdx, ...
+    featureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ...
+    newKeyFrameAdded, lastKeyFrameIndex, currFrameIndex, numSkipFrames, numPointsKeyFrame)
+%helperTrackLocalMap Refine camera pose by tracking the local map
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+%
+%   Inputs
+%   ------
+%   mapPoints         - A worldpointset object storing map points
+%   vSetKeyFrames     - An imageviewset storing key frames
+%   mapPointsIndices  - Indices of map points observed in the current frame
+%   featureIndices    - Indices of features in the current frame 
+%                       corresponding to map points denoted by mapPointsIndices                      
+%   currPose          - Current camera pose
+%   currFeatures      - ORB Features in the current frame 
+%   currPoints        - Feature points in the current frame
+%   intrinsics        - Camera intrinsics 
+%   scaleFactor       - scale factor of features
+%   numLevels         - number of levels in feature exatraction
+%   newKeyFrameAdded  - A boolean scalar indicating if a new key frame is
+%                       added recently
+%   lastKeyFrameIndex - Frame index of the last key frame
+%   currFrameIndex    - Frame index of the current frame
+%   numSkipFrames     - Largest number of frames to skip
+%   numPointsKeyFrame - Minimum number of points tracked by a key frame
+%   
+%   Outputs
+%   -------
+%   localKeyFrameIds  - ViewIds of the local key frames 
+%   currPose          - Refined camera pose of the current frame
+%   mapPointIdx       - Indices of map points observed in the current frame
+%   featureIdx        - Indices of features in the current frame corresponding
+%                       to mapPointIdx
+%   isKeyFrame        - A boolean scalar indicating if the current frame is
+%                       a key frame
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+persistent numPointsRefKeyFrame localPointsIndices localKeyFrameIdsInternal
+
+if isempty(numPointsRefKeyFrame) || newKeyFrameAdded
+    [localPointsIndices, localKeyFrameIdsInternal, numPointsRefKeyFrame] = ...
+    updateRefKeyFrameAndLocalPoints(mapPoints, vSetKeyFrames, mapPointIdx);
+end
+
+% Project the map into the frame and search for more map point correspondences
+newMapPointIdx = setdiff(localPointsIndices, mapPointIdx, 'stable');
+localFeatures  = getFeatures(mapPoints, vSetKeyFrames.Views, newMapPointIdx); 
+[projectedPoints, inlierIndex, predictedScales, viewAngles] = removeOutlierMapPoints(mapPoints, ...
+    currPose, intrinsics, newMapPointIdx, scaleFactor, numLevels);
+
+newMapPointIdx = newMapPointIdx(inlierIndex);
+localFeatures  = localFeatures(inlierIndex,:);
+
+unmatchedfeatureIdx = setdiff(cast((1:size( currFeatures.Features, 1)).', 'uint32'), ...
+    featureIdx,'stable');
+unmatchedFeatures   = currFeatures.Features(unmatchedfeatureIdx, :);
+unmatchedValidPoints= currPoints(unmatchedfeatureIdx);
+
+% Search radius depends on scale and view direction
+searchRadius    = 4*ones(size(localFeatures, 1), 1);
+searchRadius(viewAngles<3) = 2.5;
+searchRadius    = searchRadius.*predictedScales;
+
+indexPairs = matchFeaturesInRadius(binaryFeatures(localFeatures),...
+    binaryFeatures(unmatchedFeatures), unmatchedValidPoints, projectedPoints, ...
+    searchRadius, 'MatchThreshold', 40, 'MaxRatio', 0.9, 'Unique', true);
+
+% Filter by scales
+isGoodScale = currPoints.Scale(indexPairs(:, 2)) >= ...
+    max(1, predictedScales(indexPairs(:, 1))/scaleFactor) & ...
+    currPoints.Scale(indexPairs(:, 2)) <= predictedScales(indexPairs(:, 1));
+indexPairs  = indexPairs(isGoodScale, :);
+
+% Refine camera pose with more 3D-to-2D correspondences
+mapPointIdx   = [newMapPointIdx(indexPairs(:,1)); mapPointIdx];
+featureIdx     = [unmatchedfeatureIdx(indexPairs(:,2)); featureIdx];
+matchedMapPoints   = mapPoints.WorldPoints(mapPointIdx,:);
+matchedImagePoints = currPoints.Location(featureIdx,:);
+
+isKeyFrame = checkKeyFrame(numPointsRefKeyFrame, lastKeyFrameIndex, ...
+    currFrameIndex, mapPointIdx, numSkipFrames, numPointsKeyFrame);
+
+localKeyFrameIds = localKeyFrameIdsInternal;
+
+if isKeyFrame
+    % Refine camera pose only if the current frame is a key frame
+    currPose = bundleAdjustmentMotion(matchedMapPoints, matchedImagePoints, ...
+        currPose, intrinsics, 'PointsUndistorted', true, ...
+        'AbsoluteTolerance', 1e-7, 'RelativeTolerance', 1e-16,'MaxIteration', 20);
+end
+end
+
+function [localPointsIndices, localKeyFrameIds, numPointsRefKeyFrame] = ...
+    updateRefKeyFrameAndLocalPoints(mapPoints, vSetKeyFrames, pointIndices)
+
+if vSetKeyFrames.NumViews == 1
+    localKeyFrameIds = vSetKeyFrames.Views.ViewId;
+    localPointsIndices = (1:mapPoints.Count)';
+    numPointsRefKeyFrame = mapPoints.Count;
+    return
+end
+
+% The reference key frame has the most covisible map points 
+viewIds = findViewsOfWorldPoint(mapPoints, pointIndices);
+refKeyFrameId = mode(vertcat(viewIds{:}));
+
+localKeyFrames = connectedViews(vSetKeyFrames, refKeyFrameId, "MaxDistance", 2);
+localKeyFrameIds = [localKeyFrames.ViewId; refKeyFrameId];
+
+pointIdx = findWorldPointsInView(mapPoints, localKeyFrameIds);
+if iscell(pointIdx)
+    numPointsRefKeyFrame = numel(pointIdx{localKeyFrameIds==refKeyFrameId});
+    localPointsIndices = sort(vertcat(pointIdx{:}));
+else
+    numPointsRefKeyFrame = numel(pointIdx);
+    localPointsIndices = sort(pointIdx);
+end
+end
+
+function features = getFeatures(mapPoints, views, mapPointIdx)
+
+% Efficiently retrieve features and image points corresponding to map points
+% denoted by mapPointIdx
+allIndices = zeros(1, numel(mapPointIdx));
+
+% ViewId and offset pair
+count = []; % (ViewId, NumFeatures)
+viewsFeatures = views.Features;
+
+for i = 1:numel(mapPointIdx)
+    index3d  = mapPointIdx(i);
+    
+    viewId   = double(mapPoints.RepresentativeViewId(index3d));
+    
+    if isempty(count)
+        count = [viewId, size(viewsFeatures{viewId},1)];
+    elseif ~any(count(:,1) == viewId)
+        count = [count; viewId, size(viewsFeatures{viewId},1)];
+    end
+    
+    idx = find(count(:,1)==viewId);
+    
+    if idx > 1
+        offset = sum(count(1:idx-1,2));
+    else
+        offset = 0;
+    end
+    allIndices(i) = mapPoints.RepresentativeFeatureIndex(index3d) + offset;
+end
+
+uIds = count(:,1);
+
+% Concatenating features and indexing once is faster than accessing via a for loop
+allFeatures = vertcat(viewsFeatures{uIds});
+features    = allFeatures(allIndices, :);
+end
+
+function [projectedPoints, inliers, predictedScales, viewAngles] = removeOutlierMapPoints(...
+    mapPoints, pose, intrinsics, localPointsIndices, scaleFactor, ...
+    numLevels)
+
+% 1) Points within the image bounds
+xyzPoints = mapPoints.WorldPoints(localPointsIndices, :);
+[projectedPoints, isInImage] = world2img(xyzPoints, pose2extr(pose), intrinsics);
+
+if isempty(projectedPoints)
+    error('Tracking failed. Try inserting new key frames more frequently.')
+end
+
+% 2) Parallax less than 60 degrees
+cameraNormVector = [0 0 1] * pose.Rotation;
+cameraToPoints   = xyzPoints - pose.Translation;
+viewDirection    = mapPoints.ViewingDirection(localPointsIndices, :);
+validByView      = sum(viewDirection.*cameraToPoints, 2) > ...
+    cosd(60)*(vecnorm(cameraToPoints, 2, 2));
+
+% 3) Distance from map point to camera center is in the range of scale
+% invariant depth
+minDist          = mapPoints.DistanceLimits(localPointsIndices,1)/scaleFactor;
+maxDist          = mapPoints.DistanceLimits(localPointsIndices,2)*scaleFactor;
+dist             = vecnorm(xyzPoints - pose.Translation, 2, 2);
+
+validByDistance  = dist > minDist & dist < maxDist;
+
+inliers          = isInImage & validByView & validByDistance;
+
+% Predicted scales
+level= ceil(log(maxDist ./ dist)./log(scaleFactor));
+level(level<0)   = 0;
+level(level>=numLevels-1) = numLevels-1;
+predictedScales  = scaleFactor.^level;
+
+% View angles
+viewAngles       = acosd(sum(cameraNormVector.*cameraToPoints, 2) ./ ...
+    vecnorm(cameraToPoints, 2, 2));
+
+predictedScales  = predictedScales(inliers);
+viewAngles       = viewAngles(inliers);
+
+projectedPoints = projectedPoints(inliers, :);
+end
+
+function isKeyFrame = checkKeyFrame(numPointsRefKeyFrame, lastKeyFrameIndex, ...
+    currFrameIndex, mapPointsIndices, numSkipFrames, numPointsKeyFrame)
+
+% More than numSkipFrames frames have passed from last key frame insertion
+tooManyNonKeyFrames = currFrameIndex > lastKeyFrameIndex + numSkipFrames;
+
+% Track less than numPointsKeyFrame map points
+tooFewMapPoints     = numel(mapPointsIndices) < numPointsKeyFrame;
+
+% Tracked map points are fewer than 90% of points tracked by
+% the reference key frame
+tooFewTrackedPoints = numel(mapPointsIndices) < 0.9 * numPointsRefKeyFrame;
+
+isKeyFrame = (tooManyNonKeyFrames || tooFewMapPoints) && tooFewTrackedPoints;
+end
\ No newline at end of file
diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMatchedFeaturesRGBD.m b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMatchedFeaturesRGBD.m
new file mode 100644
index 0000000000000000000000000000000000000000..5aec70402a9a02803db91acb4e292a4e577e49cb
--- /dev/null
+++ b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMatchedFeaturesRGBD.m
@@ -0,0 +1,56 @@
+classdef helperVisualizeMatchedFeaturesRGBD < handle
+%helperVisualizeMatchedFeaturesRGBD show the matched features in a frame
+%
+%   This is an example helper class that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2021 The MathWorks, Inc.
+
+    properties (Access = private)
+        Image
+        
+        Feature
+    end
+    
+    methods (Access = public)
+        
+        function obj = helperVisualizeMatchedFeaturesRGBD(I1, I2, points)
+            
+            % Plot image
+            hFig  = figure;
+            hAxes = newplot(hFig); 
+            
+            % Set figure visibility and position
+            hFig.Visible = 'on';
+            movegui(hFig, [200 200]);
+            
+            % Show the image and features
+            obj.Image = showMatchedFeatures(I1, I2, points, ...
+                points, 'montage', 'Parent', hAxes, ...
+                'PlotOptions', {'g+','g+',''});
+            title(hAxes, 'Matched Features in Current Frame');
+            hold(hAxes, 'on');
+            
+            obj.Feature = findobj(hAxes.Parent,'Type','Line'); 
+        end 
+        
+        function updatePlot(obj, I1, I2, points)
+            
+            % Color and depth image
+            obj.Image.CData = imfuse(I1, I2, 'montage');
+            
+            % Connecting lines
+            obj.Feature(1).XData = NaN;
+            obj.Feature(1).YData = NaN;
+            
+            % Right image
+            obj.Feature(2).XData = points.Location(:,1) + size(I1, 2);
+            obj.Feature(2).YData = points.Location(:,2);
+            
+            % Left image
+            obj.Feature(3).XData = points.Location(:,1);
+            obj.Feature(3).YData = points.Location(:,2);
+            drawnow limitrate
+        end
+    end
+end
\ No newline at end of file
diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMotionAndStructure.m b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMotionAndStructure.m
new file mode 100644
index 0000000000000000000000000000000000000000..b064c0480c02a1f23f6c64ff7d6a4dfe3c723953
--- /dev/null
+++ b/src/main/java/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMotionAndStructure.m
@@ -0,0 +1,156 @@
+classdef helperVisualizeMotionAndStructure < handle
+%helperVisualizeMatchedFeatures show map points and camera trajectory
+%
+%   This is an example helper class that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+    properties
+        XLim = [-1.5 1.5]
+        
+        YLim = [-1 0.5]
+        
+        ZLim = [-0.5 2]
+        
+        Axes
+    end
+    
+    properties (Access = private)
+        MapPointsPlot
+ 
+        EstimatedTrajectory
+        
+        OptimizedTrajectory
+
+        CameraPlot
+    end
+
+    methods (Access = public)
+        function obj = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPoints, varargin)
+
+            if nargin > 2
+                obj.XLim = varargin{1};
+                obj.YLim = varargin{2};
+                obj.ZLim = varargin{3};
+            end
+        
+            [xyzPoints, currPose, trajectory]  = retrievePlottedData(obj, vSetKeyFrames, mapPoints);
+             
+            obj.MapPointsPlot = pcplayer(obj.XLim, obj.YLim, obj.ZLim, ...
+                'VerticalAxis', 'y', 'VerticalAxisDir', 'down');
+            
+            obj.Axes  = obj.MapPointsPlot.Axes;
+            obj.MapPointsPlot.view(xyzPoints); 
+            obj.Axes.Children.DisplayName = 'Map points';
+            
+            hold(obj.Axes, 'on');
+            
+            % Set figure position on the screen
+            movegui(obj.Axes.Parent, [1000 200]);
+            
+            % Plot camera trajectory
+            obj.EstimatedTrajectory = plot3(obj.Axes, trajectory(:,1), trajectory(:,2), ...
+                trajectory(:,3), 'r', 'LineWidth', 2 , 'DisplayName', 'Estimated trajectory');
+            
+            % Plot the current cameras
+            obj.CameraPlot = plotCamera(currPose, 'Parent', obj.Axes, 'Size', 0.05);
+        end
+        
+        function updatePlot(obj, vSetKeyFrames, mapPoints)
+            
+            [xyzPoints, currPose, trajectory]  = retrievePlottedData(obj, vSetKeyFrames, mapPoints);
+            
+            % Update the point cloud
+            obj.MapPointsPlot.view(xyzPoints);
+            
+            % Update the camera trajectory
+            set(obj.EstimatedTrajectory, 'XData', trajectory(:,1), 'YData', ...
+                trajectory(:,2), 'ZData', trajectory(:,3));
+            
+            % Update the current camera pose since the first camera is fixed
+            obj.CameraPlot.AbsolutePose = currPose.AbsolutePose;
+            obj.CameraPlot.Label        = num2str(currPose.ViewId);
+            
+            drawnow limitrate
+        end
+        
+        function plotOptimizedTrajectory(obj, poses)
+            
+            % Delete the camera plot
+            delete(obj.CameraPlot);
+            
+            % Plot the optimized trajectory
+            trans = vertcat(poses.AbsolutePose.Translation);
+            obj.OptimizedTrajectory = plot3(obj.Axes, trans(:, 1), trans(:, 2), trans(:, 3), 'm', ...
+                'LineWidth', 2, 'DisplayName', 'Optimized trajectory');
+        end
+        
+        function plotActualTrajectory(obj, gTruth, optimizedPoses)
+            estimatedCams = vertcat(optimizedPoses.AbsolutePose.Translation);
+            actualCams    = vertcat(gTruth.Translation);
+            scale = median(vecnorm(actualCams, 2, 2))/ median(vecnorm(estimatedCams, 2, 2));
+            
+            % Update the plot based on the ground truth
+            updatePlotScale(obj, scale);
+            
+            % Plot the ground truth
+            plot3(obj.Axes, actualCams(:,1), actualCams(:,2), actualCams(:,3), ...
+                'g','LineWidth',2, 'DisplayName', 'Actual trajectory');
+            
+            drawnow limitrate
+        end
+        
+        function showLegend(obj)
+            % Add a legend to the axes
+            hLegend = legend(obj.Axes, 'Location',  'northeast', ...
+                'TextColor', [1 1 1], 'FontWeight', 'bold');
+        end
+    end
+    
+    methods (Access = private)
+        function [xyzPoints, currPose, trajectory]  = retrievePlottedData(obj, vSetKeyFrames, mapPoints)
+            camPoses    = poses(vSetKeyFrames);
+            currPose    = camPoses(end,:); % Contains both ViewId and Pose
+
+            % Ensure the rotation matrix is a rigid transformation
+            R = double(currPose.AbsolutePose.R);
+            t = double(currPose.AbsolutePose.Translation);
+            [U, ~, V] = svd(R);
+            currPose.AbsolutePose.A = eye(4);
+            currPose.AbsolutePose.A(1:3, 4) = t;
+            currPose.AbsolutePose.A(1:3, 1:3) = U * V';
+
+            trajectory  = vertcat(camPoses.AbsolutePose.Translation);
+            xyzPoints   = mapPoints.WorldPoints;
+            
+            % Only plot the points within the limit
+            inPlotRange = xyzPoints(:, 1) > obj.XLim(1) & ...
+                xyzPoints(:, 1) < obj.XLim(2) & xyzPoints(:, 2) > obj.YLim(1) & ...
+                xyzPoints(:, 2) < obj.YLim(2) & xyzPoints(:, 3) > obj.ZLim(1) & ...
+                xyzPoints(:, 3) < obj.ZLim(2);
+            xyzPoints   = xyzPoints(inPlotRange, :);
+        end
+        
+        function updatePlotScale(obj, scale)
+            % Update the map points and camera trajectory based on the
+            % ground truth scale
+            obj.Axes.XLim = obj.Axes.XLim * scale;
+            obj.Axes.YLim = obj.Axes.YLim * scale;
+            obj.Axes.ZLim = obj.Axes.ZLim * scale;
+            
+            % Map points
+            obj.Axes.Children(end).XData = obj.Axes.Children(end).XData * scale;
+            obj.Axes.Children(end).YData = obj.Axes.Children(end).YData * scale;
+            obj.Axes.Children(end).ZData = obj.Axes.Children(end).ZData * scale;
+            
+            % Estiamted and optimized Camera trajectory
+            obj.EstimatedTrajectory.XData =  obj.EstimatedTrajectory.XData * scale;
+            obj.EstimatedTrajectory.YData =  obj.EstimatedTrajectory.YData * scale;
+            obj.EstimatedTrajectory.ZData =  obj.EstimatedTrajectory.ZData * scale;
+            obj.OptimizedTrajectory.XData =  obj.OptimizedTrajectory.XData * scale;
+            obj.OptimizedTrajectory.YData =  obj.OptimizedTrajectory.YData * scale;
+            obj.OptimizedTrajectory.ZData =  obj.OptimizedTrajectory.ZData * scale;
+        end
+    end
+end
\ No newline at end of file
diff --git a/src/main/java/vslam/Mathworks_VSLAM_RGBD/orbslamGroundTruth.mat b/src/main/java/vslam/Mathworks_VSLAM_RGBD/orbslamGroundTruth.mat
new file mode 100644
index 0000000000000000000000000000000000000000..ea1360e39c14cb70268bf6d6d4202b51eaf02014
Binary files /dev/null and b/src/main/java/vslam/Mathworks_VSLAM_RGBD/orbslamGroundTruth.mat differ
diff --git a/src/main/java/vslam/optimizedPoses.mat b/src/main/java/vslam/optimizedPoses.mat
new file mode 100644
index 0000000000000000000000000000000000000000..6530e386046ec69988fdea2577708629bed7c6c0
Binary files /dev/null and b/src/main/java/vslam/optimizedPoses.mat differ
diff --git a/src/main/java/vslam/pointCloudsAll.mat b/src/main/java/vslam/pointCloudsAll.mat
new file mode 100644
index 0000000000000000000000000000000000000000..2dd6354ae44726ad71a8a2d85eea456fd8a3c93e
Binary files /dev/null and b/src/main/java/vslam/pointCloudsAll.mat differ
diff --git a/src/main/java/vslam/vslam_implementation.m b/src/main/java/vslam/vslam_implementation.m
index 129fad613feb939b93075a5437f86b043feb015e..bfe1485ae3071229eee3b22daa230a5c6bfbce34 100644
--- a/src/main/java/vslam/vslam_implementation.m
+++ b/src/main/java/vslam/vslam_implementation.m
@@ -308,13 +308,13 @@ function worldPointSetOutput = ProcessImageSequence(imds)
         mapPointSet = updateRepresentativeView(mapPointSet, mapPointIdx, vSetKeyFrames.Views);
     
         % Check if the KeyFrames directory exists; if not, create it
-        keyFramesDir = './KeyFrames';
+        keyFramesDir = './KeyFrames_Mono';
         if ~exist(keyFramesDir, 'dir')
             mkdir(keyFramesDir);
         end
 
         % Store feature locations for this key frame
-        keyFramePointsDir = './KeyFramePoints';
+        keyFramePointsDir = './KeyFramePoints_Mono';
         if ~exist(keyFramePointsDir, 'dir')
             mkdir(keyFramePointsDir); 
         end
@@ -363,24 +363,24 @@ function worldPointSetOutput = ProcessImageSequence(imds)
 
     %% Optimizing
     if isLoopClosed
-    % Optimize the poses
-    minNumMatches      = 20;
-    vSetKeyFramesOptim = optimizePoses(vSetKeyFrames, minNumMatches, Tolerance=1e-16);
-
-    % Update map points after optimizing the poses
-    mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim);
-
-    updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
-
-    % Plot the optimized camera trajectory
-    optimizedPoses  = poses(vSetKeyFramesOptim);
-    plotOptimizedTrajectory(mapPlot, optimizedPoses)
-
-    % Update legend
-    showLegend(mapPlot);
-
-    worldPointSetOutput = mapPointSet;
-end
+        % Optimize the poses
+        minNumMatches      = 20;
+        vSetKeyFramesOptim = optimizePoses(vSetKeyFrames, minNumMatches, Tolerance=1e-16);
+    
+        % Update map points after optimizing the poses
+        mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim);
+    
+        updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
+    
+        % Plot the optimized camera trajectory
+        optimizedPoses  = poses(vSetKeyFramesOptim);
+        plotOptimizedTrajectory(mapPlot, optimizedPoses)
+    
+        % Update legend
+        showLegend(mapPlot);
+    
+        worldPointSetOutput = mapPointSet;
+    end
     
 end
 
diff --git a/src/main/java/vslam/vslam_implementation_rgbd.asv b/src/main/java/vslam/vslam_implementation_rgbd.asv
new file mode 100644
index 0000000000000000000000000000000000000000..875a7b2b4156ef690e3cd415ca2c176d3dc9e67e
--- /dev/null
+++ b/src/main/java/vslam/vslam_implementation_rgbd.asv
@@ -0,0 +1,181 @@
+function worldPointSet = vslam_implementation_rgbd(dataset_name)
+
+    baseFolder = './'
+    datasetFolder = [baseFolder, dataset_name, '/'];
+
+    if ~exist(datasetFolder, 'dir')
+        if(dataset_name == 'tum_rgbd_dataset')
+    
+            % Download if the dataset is not already downloaded
+    
+            
+            baseDownloadURL = "https://cvg.cit.tum.de/rgbd/dataset/freiburg3/rgbd_dataset_freiburg3_long_office_household.tgz"; 
+            dataFolder      = fullfile(tempdir, 'tum_rgbd_dataset', filesep); 
+            options         = weboptions('Timeout', Inf);
+            tgzFileName     = [dataFolder, 'fr3_office.tgz'];
+            folderExists    = exist(dataFolder, 'dir');
+            
+            % Create a folder in a temporary directory to save the downloaded file
+            if ~folderExists  
+                mkdir(dataFolder); 
+                disp('Downloading fr3_office.tgz (1.38 GB). This download can take a few minutes.') 
+                websave(tgzFileName, baseDownloadURL, options); 
+                
+                % Extract contents of the downloaded file
+                disp('Extracting fr3_office.tgz (1.38 GB) ...') 
+                untar(tgzFileName, dataFolder); 
+            end
+        
+            imageFolder = [dataFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        end
+    else
+        if (dataset_name == 'tum_rgbd_dataset')
+            imageFolder = [datasetFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        end
+    end
+
+
+
+    % Import dependencies
+    addpath('./Mathworks_VSLAM_RGBD/');
+
+    % Initialize image dataset
+    imgFolderColor = [imageFolder,'rgb/'];
+    imgFolderDepth = [imageFolder,'depth/'];
+    imdsColor      = imageDatastore(imgFolderColor);
+    imdsDepth      = imageDatastore(imgFolderDepth);
+    
+    
+    % Process the image sequence
+    worldPointSet = ProcessImageSequence(imdsColor, imdsDepth);
+end
+
+function worldPointSetOutput = ProcessImageSequence(imdsColor, imdsDepth)
+    
+    
+end
+
+%% Helper functions
+
+% helperImportTimestampFile Import time stamp file
+
+function timestamp = helperImportTimestampFile(filename)
+    % Input handling
+    dataLines = [4, Inf];
+    
+    %% Set up the Import Options and import the data
+    opts = delimitedTextImportOptions("NumVariables", 2);
+    
+    % Specify range and delimiter
+    opts.DataLines = dataLines;
+    opts.Delimiter = " ";
+    
+    % Specify column names and types
+    opts.VariableNames = ["VarName1", "Var2"];
+    opts.SelectedVariableNames = "VarName1";
+    opts.VariableTypes = ["double", "string"];
+    
+    % Specify file level properties
+    opts.ExtraColumnsRule = "ignore";
+    opts.EmptyLineRule = "read";
+    opts.ConsecutiveDelimitersRule = "join";
+    opts.LeadingDelimitersRule = "ignore";
+    
+    % Specify variable properties
+    opts = setvaropts(opts, "Var2", "WhitespaceRule", "preserve");
+    opts = setvaropts(opts, "Var2", "EmptyFieldRule", "auto");
+    
+    % Import the data
+    data = readtable(filename, opts);
+    
+    % Convert to output type
+    timestamp = table2array(data);
+end
+
+% helperAlignTimestamp align time stamp of color and depth images.
+function indexPairs = helperAlignTimestamp(timeColor, timeDepth)
+    idxDepth = 1;
+    indexPairs = zeros(numel(timeColor), 2);
+    for i = 1:numel(timeColor)
+        for j = idxDepth : numel(timeDepth)
+            if abs(timeColor(i) - timeDepth(j)) < 1e-4
+                idxDepth = j;
+                indexPairs(i, :) = [i, j];
+                break
+            elseif timeDepth(j) - timeColor(i) > 1e-3
+                break
+            end
+        end
+    end
+    indexPairs = indexPairs(indexPairs(:,1)>0, :);
+end
+
+% helperDetectAndExtractFeatures detect and extract and ORB features from the image.
+function [features, validPoints] = helperDetectAndExtractFeatures(Irgb, scaleFactor, numLevels)
+ 
+    numPoints = 1000;
+    
+    % Detect ORB features
+    Igray  = rgb2gray(Irgb);
+    
+    points = detectORBFeatures(Igray, ScaleFactor=scaleFactor, NumLevels=numLevels);
+    
+    % Select a subset of features, uniformly distributed throughout the image
+    points = selectUniform(points, numPoints, size(Igray, 1:2));
+    
+    % Extract features
+    [features, validPoints] = extractFeatures(Igray, points);
+end
+
+% helperReconstructFromRGBD reconstruct scene from color and depth image.
+
+function [xyzPoints, validIndex] = helperReconstructFromRGBD(points, ...
+    depthMap, intrinsics, currPose, depthFactor)
+
+    ptcloud = pcfromdepth(depthMap,depthFactor,intrinsics,ImagePoints=points, DepthRange=[0.1, 5]);
+    
+    isPointValid = ~isnan(ptcloud.Location(:, 1));
+    xyzPoints    = ptcloud.Location(isPointValid, :);
+    xyzPoints    = transformPointsForward(currPose, xyzPoints);
+    validIndex   = find(isPointValid);
+end
+
+% helperCullRecentMapPoints cull recently added map points.
+function [mapPointSet, mapPointsIdx] = ...
+    helperCullRecentMapPoints(mapPointSet, mapPointsIdx, newPointIdx, rgbdMapPointsIndices)
+    outlierIdx = setdiff([newPointIdx; rgbdMapPointsIndices], mapPointsIdx);
+    if ~isempty(outlierIdx)
+        mapPointSet   = removeWorldPoints(mapPointSet, outlierIdx);
+        mapPointsIdx  = mapPointsIdx - arrayfun(@(x) nnz(x>outlierIdx), mapPointsIdx);
+    end
+end
+
+% helperEstimateTrajectoryError calculate the tracking error.
+function rmse = helperEstimateTrajectoryError(gTruth, cameraPoses)
+    locations       = vertcat(cameraPoses.AbsolutePose.Translation);
+    gLocations      = vertcat(gTruth.Translation);
+    scale           = median(vecnorm(gLocations, 2, 2))/ median(vecnorm(locations, 2, 2));
+    scaledLocations = locations * scale;
+    
+    rmse = sqrt(mean( sum((scaledLocations - gLocations).^2, 2) ));
+    disp(['Absolute RMSE for key frame trajectory (m): ', num2str(rmse)]);
+end
+
+% helperUpdateGlobalMap update 3-D locations of map points after pose graph optimization
+function mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim)
+
+    posesOld     = vSetKeyFrames.Views.AbsolutePose;
+    posesNew     = vSetKeyFramesOptim.Views.AbsolutePose;
+    positionsOld = mapPointSet.WorldPoints;
+    positionsNew = positionsOld;
+    indices = 1:mapPointSet.Count;
+    
+    % Update world location of each map point based on the new absolute pose of 
+    % the corresponding major view
+    for i = 1: mapPointSet.Count
+        majorViewIds = mapPointSet.RepresentativeViewId(i);
+        tform = rigidtform3d(posesNew(majorViewIds).A/posesOld(majorViewIds).A);
+        positionsNew(i, :) = transformPointsForward(tform, positionsOld(i, :));
+    end
+    mapPointSet = updateWorldPoints(mapPointSet, indices, positionsNew);
+end
diff --git a/src/main/java/vslam/vslam_implementation_rgbd.m b/src/main/java/vslam/vslam_implementation_rgbd.m
new file mode 100644
index 0000000000000000000000000000000000000000..ad7cd6a06ec6f0126c036618b17892b74f14901d
--- /dev/null
+++ b/src/main/java/vslam/vslam_implementation_rgbd.m
@@ -0,0 +1,544 @@
+function [worldPointSetOutput, optimizedPoses, pointCloudsAll] = vslam_implementation_rgbd(dataset_name)
+    % Define the base folder for datasets
+    baseFolder = './';
+    datasetFolder = [baseFolder, dataset_name, '/'];
+
+    % Check if the dataset exists, if not download and prepare it
+    if ~exist(datasetFolder, 'dir')
+        if strcmp(dataset_name, 'tum_rgbd_dataset')
+            % Define the URL and local folder for download
+            baseDownloadURL = "https://cvg.cit.tum.de/rgbd/dataset/freiburg3/rgbd_dataset_freiburg3_long_office_household.tgz";
+            dataFolder = fullfile(baseFolder, 'tum_rgbd_dataset', filesep);
+            tgzFileName = [dataFolder, 'fr3_office.tgz'];
+
+            % Create a folder to save the downloaded file
+            if ~exist(dataFolder, 'dir')
+                mkdir(dataFolder);
+                disp('Downloading fr3_office.tgz (1.38 GB). This download can take a few minutes.');
+                h = waitbar(0, 'Downloading Dataset... Please wait.', 'Name', 'Downloading fr3_office');
+                websave(tgzFileName, baseDownloadURL, weboptions('Timeout', Inf));
+                % Update and close waitbar after download completes
+                waitbar(1, h, 'Download Complete. Extracting...');
+                pause(1); % Pause to show complete message
+                close(h);
+
+                % Extract contents of the downloaded file
+                disp('Extracting fr3_office.tgz (1.38 GB) ...');
+                h = waitbar(0, 'Extracting files... This may take a while.', 'Name', 'Extracting Data');
+                untar(tgzFileName, dataFolder);
+
+                % Close waitbar after extraction completes
+                waitbar(1, h, 'Extraction Complete.');
+                pause(1); % Pause to show complete message
+                close(h);
+            end
+
+            imageFolder = [dataFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        else
+            error('Dataset name not recognized or dataset-specific download steps not defined.');
+        end
+    else
+        % If dataset is already present, set the image folder path
+        if strcmp(dataset_name, 'tum_rgbd_dataset')
+            imageFolder = [datasetFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        end
+    end
+
+    % Import dependencies
+    addpath('./Mathworks_VSLAM_RGBD/');
+
+    % Initialize image dataset stores for color and depth images
+    imgFolderColor = [imageFolder, 'rgb/'];
+    imgFolderDepth = [imageFolder, 'depth/'];
+    imdsColor = imageDatastore(imgFolderColor);
+    imdsDepth = imageDatastore(imgFolderDepth);
+
+    % Note that the color and depth images are generated in an un-synchronized way in the dataset. Therefore, we need to associate color images to depth images based on the time stamp.
+    % Load time stamp data of color images
+    timeColor = helperImportTimestampFile([imageFolder, 'rgb.txt']);
+    
+    % Load time stamp data of depth images
+    timeDepth = helperImportTimestampFile([imageFolder, 'depth.txt']);
+    
+    % Align the time stamp
+    indexPairs = helperAlignTimestamp(timeColor, timeDepth);
+    
+    % Select the synchronized image data
+    imdsColor     = subset(imdsColor, indexPairs(:, 1));
+    imdsDepth     = subset(imdsDepth, indexPairs(:, 2));
+
+    % Process the image sequence
+    [worldPointSetOutput, optimizedPoses, pointCloudsAll] = ProcessImageSequence(imdsColor, imdsDepth);
+
+    % Save the outputs to .mat files
+    save('worldPointSetOutput.mat', 'worldPointSetOutput');
+    save('optimizedPoses.mat', 'optimizedPoses');
+    save('pointCloudsAll.mat', 'pointCloudsAll');
+
+end
+
+
+function [worldPointSetOutput, optimizedPoses, pointCloudsAll] = ProcessImageSequence(imdsColor, imdsDepth)
+    % Inspect the first RGB-D image
+    currFrameIdx  = 1;
+    currIcolor    = readimage(imdsColor, currFrameIdx);
+    currIdepth    = readimage(imdsDepth, currFrameIdx);
+    imshowpair(currIcolor, currIdepth, "montage");
+    
+    % Map Initialization: The pipeline starts by initializing the map that holds 3-D world points. 
+    % This step is crucial and has a significant impact on the accuracy of the final SLAM result. 
+    % Initial ORB feature points are extracted from the first color image using helperDetectAndExtractFeatures. 
+    % Their corresponding 3-D world locations can be computed from the pixel coordinates of the feature 
+    % points and the depth value using helperReconstructFromRGBD.
+
+    % Set random seed for reproducibility
+    rng(0);
+    
+    % Create a cameraIntrinsics object to store the camera intrinsic parameters.
+    % The intrinsics for the dataset can be found at the following page:
+    % https://vision.in.tum.de/data/datasets/rgbd-dataset/file_formats
+    focalLength    = [535.4, 539.2];    % in units of pixels
+    principalPoint = [320.1, 247.6];    % in units of pixels
+    imageSize      = size(currIcolor,[1,2]); % in pixels [mrows, ncols]
+    depthFactor    = 5e3;
+    intrinsics     = cameraIntrinsics(focalLength,principalPoint,imageSize);
+    
+    % Detect and extract ORB features from the color image
+    scaleFactor = 1.2;
+    numLevels   = 8;
+    [currFeatures, currPoints] = helperDetectAndExtractFeatures(currIcolor, scaleFactor, numLevels); 
+    
+    initialPose = rigidtform3d();
+    [xyzPoints, validIndex] = helperReconstructFromRGBD(currPoints, currIdepth, intrinsics, initialPose, depthFactor);
+
+    % Initialize Place Recognition Database
+    % Loop detection is performed using the bags-of-words approach. A visual vocabulary represented as a bagOfFeatures object is created offline with the ORB descriptors extracted from a large set of images in the dataset by calling:
+    % bag = bagOfFeatures(imds,CustomExtractor=@helperORBFeatureExtractorFunction, TreeProperties=[5, 10], StrongestFeatures=1);
+    % where imds is an imageDatastore object storing the training images and helperORBFeatureExtractorFunction is the ORB feature extractor function. See Image Retrieval with Bag of Visual Words for more information.
+    % The loop closure process incrementally builds a database, represented as an invertedImageIndex object, that stores the visual word-to-image mapping based on the bag of ORB features.
+
+    % Load the bag of features data created offline
+    bofData         = load("bagOfFeaturesDataSLAM.mat");
+    
+    % Initialize the place recognition database
+    loopDatabase    = invertedImageIndex(bofData.bof, SaveFeatureLocations=false);
+    
+    % Add features of the first key frame to the database
+    currKeyFrameId = 1;
+    addImageFeatures(loopDatabase, currFeatures, currKeyFrameId);
+
+    % Data Management and Visualization
+    % After the map is initialized using the first pair of color and depth image, you can use imageviewset and worldpointset to store the first key frames and the corresponding map points:
+
+    % Create an empty imageviewset object to store key frames
+    vSetKeyFrames = imageviewset;
+    
+    % Create an empty worldpointset object to store 3-D map points
+    mapPointSet   = worldpointset;
+    
+    % Add the first key frame
+    vSetKeyFrames = addView(vSetKeyFrames, currKeyFrameId, initialPose, Points=currPoints,...
+        Features=currFeatures.Features);
+    
+    % Add 3-D map points
+    [mapPointSet, rgbdMapPointsIdx] = addWorldPoints(mapPointSet, xyzPoints);
+    
+    % Add observations of the map points
+    mapPointSet = addCorrespondences(mapPointSet, currKeyFrameId, rgbdMapPointsIdx, validIndex);
+    
+    % Update view direction and depth
+    mapPointSet = updateLimitsAndDirection(mapPointSet, rgbdMapPointsIdx, vSetKeyFrames.Views);
+    
+    % Update representative view
+    mapPointSet = updateRepresentativeView(mapPointSet, rgbdMapPointsIdx, vSetKeyFrames.Views);
+    
+    % Visualize matched features in the first key frame
+    featurePlot = helperVisualizeMatchedFeaturesRGBD(currIcolor, currIdepth, currPoints(validIndex));
+    
+    % Visualize initial map points and camera trajectory
+    xLim = [-4 4];
+    yLim = [-3 1];
+    zLim = [-1 6];
+    mapPlot  = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPointSet, xLim, yLim, zLim);
+    
+    % Show legend
+    showLegend(mapPlot);
+
+    % Tracking
+    % The tracking process is performed using every RGB-D image and determines when to insert a new key frame. 
+    % ViewId of the last key frame
+    lastKeyFrameId    = currKeyFrameId;
+    
+    % Index of the last key frame in the input image sequence
+    lastKeyFrameIdx   = currFrameIdx; 
+    
+    % Indices of all the key frames in the input image sequence
+    addedFramesIdx    = lastKeyFrameIdx;
+    
+    currFrameIdx      = 2;
+    isLoopClosed      = false;
+
+    % Each frame is processed as follows:
+    % ORB features are extracted for each new color image and then matched (using matchFeatures), with features in the last key frame that have known corresponding 3-D map points.
+    % Estimate the camera pose using Perspective-n-Point algorithm, which estimates the pose of a calibrated camera given a set of 3-D points and their corresponding 2-D projections using estworldpose.
+    % Given the camera pose, project the map points observed by the last key frame into the current frame and search for feature correspondences using  matchFeaturesInRadius.
+    % With 3-D to 2-D correspondences in the current frame, refine the camera pose by performing a motion-only bundle adjustment using bundleAdjustmentMotion.
+    % Project the local map points into the current frame to search for more feature correspondences using matchFeaturesInRadius and refine the camera pose again using bundleAdjustmentMotion.
+    % The last step of tracking is to decide if the current frame should be a new key frame. A frame is a key frame if both of the following conditions are satisfied:
+    % At least 20 frames have passed since the last key frame or the current frame tracks fewer than 100 map points or 25% of points tracked by the reference key frame.
+    % The map points tracked by the current frame are fewer than 90% of points tracked by the reference key frame.
+    % If the current frame is to become a key frame, continue to the Local Mapping process. Otherwise, start Tracking for the next frame.
+    
+    % Main loop
+    isLastFrameKeyFrame = true;
+    while ~isLoopClosed && currFrameIdx < numel(imdsColor.Files)
+    
+        currIcolor = readimage(imdsColor, currFrameIdx);
+        currIdepth = readimage(imdsDepth, currFrameIdx);
+    
+        [currFeatures, currPoints]    = helperDetectAndExtractFeatures(currIcolor, scaleFactor, numLevels);
+    
+        % Track the last key frame
+        % trackedMapPointsIdx:  Indices of the map points observed in the current left frame 
+        % trackedFeatureIdx:    Indices of the corresponding feature points in the current left frame
+        [currPose, trackedMapPointsIdx, trackedFeatureIdx] = helperTrackLastKeyFrame(mapPointSet, ...
+            vSetKeyFrames.Views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor);
+        
+        if isempty(currPose) || numel(trackedMapPointsIdx) < 30
+            currFrameIdx = currFrameIdx + 1;
+            continue
+        end
+        
+        % Track the local map and check if the current frame is a key frame.
+        % A frame is a key frame if both of the following conditions are satisfied:
+        %
+        % 1. At least 20 frames have passed since the last key frame or the 
+        %    current frame tracks fewer than 100 map points. 
+        % 2. The map points tracked by the current frame are fewer than 90% of 
+        %    points tracked by the reference key frame.
+        %
+        % localKeyFrameIds:   ViewId of the connected key frames of the current frame
+        numSkipFrames     = 20;
+        numPointsKeyFrame = 100;
+        [localKeyFrameIds, currPose, trackedMapPointsIdx, trackedFeatureIdx, isKeyFrame] = ...
+            helperTrackLocalMap(mapPointSet, vSetKeyFrames, trackedMapPointsIdx, ...
+            trackedFeatureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ...
+            isLastFrameKeyFrame, lastKeyFrameIdx, currFrameIdx, numSkipFrames, numPointsKeyFrame);
+    
+        % Visualize matched features
+        updatePlot(featurePlot, currIcolor, currIdepth, currPoints(trackedFeatureIdx));
+        
+        if ~isKeyFrame
+            currFrameIdx = currFrameIdx + 1;
+            isLastFrameKeyFrame = false;
+            continue
+        else
+            % Match feature points between the stereo images and get the 3-D world positions
+            [xyzPoints, validIndex] = helperReconstructFromRGBD(currPoints, currIdepth, ...
+                intrinsics, currPose, depthFactor);
+    
+            [untrackedFeatureIdx, ia] = setdiff(validIndex, trackedFeatureIdx);
+            xyzPoints = xyzPoints(ia, :);
+            isLastFrameKeyFrame = true;
+        end
+    
+        % Update current key frame ID
+        currKeyFrameId  = currKeyFrameId + 1;
+
+        % Local Mapping
+        % Local mapping is performed for every key frame. When a new key frame is determined, add it to the key frames and update the attributes of the map points observed by the new key frame. To ensure that mapPointSet contains as few outliers as possible, a valid map point must be observed in at least 3 key frames. 
+        % New map points are created by triangulating ORB feature points in the current key frame and its connected key frames. For each unmatched feature point in the current key frame, search for a match with other unmatched points in the connected key frames using matchFeatures. The local bundle adjustment refines the pose of the current key frame, the poses of connected key frames, and all the map points observed in these key frames.
+
+        % Add the new key frame    
+        [mapPointSet, vSetKeyFrames] = helperAddNewKeyFrame(mapPointSet, vSetKeyFrames, ...
+            currPose, currFeatures, currPoints, trackedMapPointsIdx, trackedFeatureIdx, localKeyFrameIds);
+            
+        % Remove outlier map points that are observed in fewer than 3 key frames
+        if currKeyFrameId == 2
+            triangulatedMapPointsIdx = [];
+        end
+        
+        [mapPointSet, trackedMapPointsIdx] = ...
+            helperCullRecentMapPoints(mapPointSet, trackedMapPointsIdx, triangulatedMapPointsIdx, ...
+            rgbdMapPointsIdx);
+        
+        % Add new map points computed from disparity 
+        [mapPointSet, rgbdMapPointsIdx] = addWorldPoints(mapPointSet, xyzPoints);
+        mapPointSet = addCorrespondences(mapPointSet, currKeyFrameId, rgbdMapPointsIdx, ...
+            untrackedFeatureIdx);
+        
+        % Create new map points by triangulation
+        minNumMatches = 10;
+        minParallax   = 0.35;
+        [mapPointSet, vSetKeyFrames, triangulatedMapPointsIdx, rgbdMapPointsIdx] = helperCreateNewMapPointsStereo( ...
+            mapPointSet, vSetKeyFrames, currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax, ...
+            untrackedFeatureIdx, rgbdMapPointsIdx);
+    
+        % Update view direction and depth
+        mapPointSet = updateLimitsAndDirection(mapPointSet, [triangulatedMapPointsIdx; rgbdMapPointsIdx], ...
+            vSetKeyFrames.Views);
+    
+        % Update representative view
+        mapPointSet = updateRepresentativeView(mapPointSet, [triangulatedMapPointsIdx; rgbdMapPointsIdx], ...
+            vSetKeyFrames.Views);
+    
+        % Local bundle adjustment
+        [mapPointSet, vSetKeyFrames, triangulatedMapPointsIdx, rgbdMapPointsIdx] = ...
+            helperLocalBundleAdjustmentStereo(mapPointSet, vSetKeyFrames, ...
+            currKeyFrameId, intrinsics, triangulatedMapPointsIdx, rgbdMapPointsIdx);
+
+        % Check if the KeyFrames directory exists; if not, create it
+        keyFramesDir = './KeyFrames';
+        if ~exist(keyFramesDir, 'dir')
+            mkdir(keyFramesDir);
+        end
+
+        % Store feature locations for this key frame
+        keyFramePointsDir = './KeyFramePoints';
+        if ~exist(keyFramePointsDir, 'dir')
+            mkdir(keyFramePointsDir); 
+        end
+
+        % Save the current key frame image using currKeyFrameId
+        filename = sprintf('%s/KeyFrame_%04d.png', keyFramesDir, currKeyFrameId);
+        imwrite(currIcolor, filename);
+
+        % Save feature points information
+        saveKeyFramePoints(keyFramePointsDir, currKeyFrameId, currPoints(trackedFeatureIdx), trackedMapPointsIdx);
+    
+        % Visualize 3-D world points and camera trajectory
+        updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
+
+        % Loop Closure
+        % The loop closure detection step takes the current key frame processed by the local mapping process and tries to detect and close the loop. Loop candidates are identified by querying images in the database that are visually similar to the current key frame using evaluateImageRetrieval. A candidate key frame is valid if it is not connected to the last key frame and three of its neighbor key frames are loop candidates.
+        % When a valid loop candidate is found, use estgeotform3d to compute the relative pose between the loop candidate frame and the current key frame. The relative pose represents a 3-D rigid transformation stored in a rigidtform3d object. Then add the loop connection with the relative pose and update mapPointSet and vSetKeyFrames.
+        % Check loop closure after some key frames have been created    
+        if currKeyFrameId > 20
+            
+            % Minimum number of feature matches of loop edges
+            loopEdgeNumMatches = 120;
+            
+            % Detect possible loop closure key frame candidates
+            [isDetected, validLoopCandidates] = helperCheckLoopClosure(vSetKeyFrames, currKeyFrameId, ...
+                loopDatabase, currIcolor, loopEdgeNumMatches);
+            
+            if isDetected 
+                % Add loop closure connections
+                maxDistance = 0.1;
+                [isLoopClosed, mapPointSet, vSetKeyFrames] = helperAddLoopConnectionsStereo(...
+                    mapPointSet, vSetKeyFrames, validLoopCandidates, currKeyFrameId, ...
+                    currFeatures, currPoints, loopEdgeNumMatches, maxDistance);
+            end
+        end
+        
+        % If no loop closure is detected, add current features into the database
+        if ~isLoopClosed
+            addImageFeatures(loopDatabase,  currFeatures, currKeyFrameId);
+        end
+        
+        % Update IDs and indices
+        lastKeyFrameId  = currKeyFrameId;
+        lastKeyFrameIdx = currFrameIdx;
+        addedFramesIdx  = [addedFramesIdx; currFrameIdx]; %#ok<AGROW>
+        currFrameIdx    = currFrameIdx + 1;
+    end % End of main loop
+
+    % Finally, apply pose graph optimization over the essential graph in vSetKeyFrames to correct the drift. The essential graph is created internally by removing connections with fewer than minNumMatches matches in the covisibility graph. After pose graph optimization, update the 3-D locations of the map points using the optimized poses.
+    
+    % Optimize the poses
+    minNumMatches      = 50;
+    vSetKeyFramesOptim = optimizePoses(vSetKeyFrames, minNumMatches, Tolerance=1e-16);
+    
+    % Update map points after optimizing the poses
+    mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim);
+    
+    updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
+    
+    % Plot the optimized camera trajectory
+    optimizedPoses  = poses(vSetKeyFramesOptim);
+    plotOptimizedTrajectory(mapPlot, optimizedPoses)
+    
+    % Update legend
+    showLegend(mapPlot);
+
+    worldPointSetOutput = mapPointSet;
+
+    % Dense Reconstruction from Depth Image
+    % Given the refined camera poses, you can reproject all the valid image points in the associated depth images back to the 3-D space to perform dense reconstruction. 
+    % Create an array of pointCloud objects to store the world points constructed
+
+    % from the key frames
+    ptClouds =  repmat(pointCloud(zeros(1, 3)), numel(addedFramesIdx), 1);
+    
+    % Ignore image points at the boundary 
+    offset = 40;
+    [X, Y] = meshgrid(offset:2:imageSize(2)-offset, offset:2:imageSize(1)-offset);
+    
+    for i = 1: numel(addedFramesIdx)
+        Icolor = readimage(imdsColor, addedFramesIdx(i));
+        Idepth = readimage(imdsDepth, addedFramesIdx(i));
+    
+        [xyzPoints, validIndex] = helperReconstructFromRGBD([X(:), Y(:)], ...
+            Idepth, intrinsics, optimizedPoses.AbsolutePose(i), depthFactor);
+    
+        colors = zeros(numel(X), 1, 'like', Icolor);
+        for j = 1:numel(X)
+            colors(j, 1:3) = Icolor(Y(j), X(j), :);
+        end
+        ptClouds(i) = pointCloud(xyzPoints, Color=colors(validIndex, :));
+    end
+    
+    % Concatenate the point clouds
+    pointCloudsAll = pccat(ptClouds);
+    
+    figure
+    pcshow(pointCloudsAll,VerticalAxis="y", VerticalAxisDir="down");
+    xlabel('X')
+    ylabel('Y')
+    zlabel('Z')
+end
+
+%% Helper functions
+
+% helperImportTimestampFile Import time stamp file
+
+function timestamp = helperImportTimestampFile(filename)
+    % Input handling
+    dataLines = [4, Inf];
+    
+    %% Set up the Import Options and import the data
+    opts = delimitedTextImportOptions("NumVariables", 2);
+    
+    % Specify range and delimiter
+    opts.DataLines = dataLines;
+    opts.Delimiter = " ";
+    
+    % Specify column names and types
+    opts.VariableNames = ["VarName1", "Var2"];
+    opts.SelectedVariableNames = "VarName1";
+    opts.VariableTypes = ["double", "string"];
+    
+    % Specify file level properties
+    opts.ExtraColumnsRule = "ignore";
+    opts.EmptyLineRule = "read";
+    opts.ConsecutiveDelimitersRule = "join";
+    opts.LeadingDelimitersRule = "ignore";
+    
+    % Specify variable properties
+    opts = setvaropts(opts, "Var2", "WhitespaceRule", "preserve");
+    opts = setvaropts(opts, "Var2", "EmptyFieldRule", "auto");
+    
+    % Import the data
+    data = readtable(filename, opts);
+    
+    % Convert to output type
+    timestamp = table2array(data);
+end
+
+% helperAlignTimestamp align time stamp of color and depth images.
+function indexPairs = helperAlignTimestamp(timeColor, timeDepth)
+    idxDepth = 1;
+    indexPairs = zeros(numel(timeColor), 2);
+    for i = 1:numel(timeColor)
+        for j = idxDepth : numel(timeDepth)
+            if abs(timeColor(i) - timeDepth(j)) < 1e-4
+                idxDepth = j;
+                indexPairs(i, :) = [i, j];
+                break
+            elseif timeDepth(j) - timeColor(i) > 1e-3
+                break
+            end
+        end
+    end
+    indexPairs = indexPairs(indexPairs(:,1)>0, :);
+end
+
+% helperDetectAndExtractFeatures detect and extract and ORB features from the image.
+function [features, validPoints] = helperDetectAndExtractFeatures(Irgb, scaleFactor, numLevels)
+ 
+    numPoints = 1000;
+    
+    % Detect ORB features
+    Igray  = rgb2gray(Irgb);
+    
+    points = detectORBFeatures(Igray, ScaleFactor=scaleFactor, NumLevels=numLevels);
+    
+    % Select a subset of features, uniformly distributed throughout the image
+    points = selectUniform(points, numPoints, size(Igray, 1:2));
+    
+    % Extract features
+    [features, validPoints] = extractFeatures(Igray, points);
+end
+
+% helperReconstructFromRGBD reconstruct scene from color and depth image.
+
+function [xyzPoints, validIndex] = helperReconstructFromRGBD(points, ...
+    depthMap, intrinsics, currPose, depthFactor)
+
+    ptcloud = pcfromdepth(depthMap,depthFactor,intrinsics,ImagePoints=points, DepthRange=[0.1, 5]);
+    
+    isPointValid = ~isnan(ptcloud.Location(:, 1));
+    xyzPoints    = ptcloud.Location(isPointValid, :);
+    xyzPoints    = transformPointsForward(currPose, xyzPoints);
+    validIndex   = find(isPointValid);
+end
+
+% helperCullRecentMapPoints cull recently added map points.
+function [mapPointSet, mapPointsIdx] = ...
+    helperCullRecentMapPoints(mapPointSet, mapPointsIdx, newPointIdx, rgbdMapPointsIndices)
+    outlierIdx = setdiff([newPointIdx; rgbdMapPointsIndices], mapPointsIdx);
+    if ~isempty(outlierIdx)
+        mapPointSet   = removeWorldPoints(mapPointSet, outlierIdx);
+        mapPointsIdx  = mapPointsIdx - arrayfun(@(x) nnz(x>outlierIdx), mapPointsIdx);
+    end
+end
+
+% helperEstimateTrajectoryError calculate the tracking error.
+function rmse = helperEstimateTrajectoryError(gTruth, cameraPoses)
+    locations       = vertcat(cameraPoses.AbsolutePose.Translation);
+    gLocations      = vertcat(gTruth.Translation);
+    scale           = median(vecnorm(gLocations, 2, 2))/ median(vecnorm(locations, 2, 2));
+    scaledLocations = locations * scale;
+    
+    rmse = sqrt(mean( sum((scaledLocations - gLocations).^2, 2) ));
+    disp(['Absolute RMSE for key frame trajectory (m): ', num2str(rmse)]);
+end
+
+% helperUpdateGlobalMap update 3-D locations of map points after pose graph optimization
+function mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim)
+
+    posesOld     = vSetKeyFrames.Views.AbsolutePose;
+    posesNew     = vSetKeyFramesOptim.Views.AbsolutePose;
+    positionsOld = mapPointSet.WorldPoints;
+    positionsNew = positionsOld;
+    indices = 1:mapPointSet.Count;
+    
+    % Update world location of each map point based on the new absolute pose of 
+    % the corresponding major view
+    for i = 1: mapPointSet.Count
+        majorViewIds = mapPointSet.RepresentativeViewId(i);
+        tform = rigidtform3d(posesNew(majorViewIds).A/posesOld(majorViewIds).A);
+        positionsNew(i, :) = transformPointsForward(tform, positionsOld(i, :));
+    end
+    mapPointSet = updateWorldPoints(mapPointSet, indices, positionsNew);
+end
+
+% CSV file creation for points within keyframe
+function saveKeyFramePoints(dirPath, keyFrameId, featurePoints, mapPointsIdx)
+    % Ensure the directory exists
+    if ~exist(dirPath, 'dir')
+        mkdir(dirPath);
+    end
+
+    % Define the filename for the CSV file
+    csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', dirPath, keyFrameId);
+
+    % Extract pixel locations from the feature points
+    pixelLocations = featurePoints.Location;  % This should be an Nx2 matrix
+
+    % Combine the indices, pixel locations, and corresponding world points indices into one matrix
+    dataMatrix = [pixelLocations, mapPointsIdx];  % Concatenate horizontally
+
+    % Write the combined data to a CSV file
+    writematrix(dataMatrix, csvFilename);
+end
diff --git a/src/main/java/vslam/worldPointSetOutput.mat b/src/main/java/vslam/worldPointSetOutput.mat
new file mode 100644
index 0000000000000000000000000000000000000000..383fec4a6a1c781837ee0bf0e9b0d4aa65556141
Binary files /dev/null and b/src/main/java/vslam/worldPointSetOutput.mat differ
diff --git a/target/classes/.DS_Store b/target/classes/.DS_Store
new file mode 100644
index 0000000000000000000000000000000000000000..bcc567b13ce12611ad4806d72e532f9ad2e84306
Binary files /dev/null and b/target/classes/.DS_Store differ
diff --git a/target/classes/README 2.md b/target/classes/README 2.md
new file mode 100644
index 0000000000000000000000000000000000000000..c93df4abbe8779abb9ad11834d608762c273d314
--- /dev/null
+++ b/target/classes/README 2.md	
@@ -0,0 +1,15 @@
+
+# Entry into System
+
+Things that are true:
+1. A student should be able to build the system, then press run, then open a localhost and see the video and the point cloud of each object
+2. A student should also be able to choose between different object and get information (need interactive display)
+3. The entry needs to do the entire workflow
+    - get keyframes and featurepoints
+    - get objects from keyframes
+    - start object detection
+    - finish object detection and update database
+    - ping GUI server
+    - GUI server pulls information and displays point cloud to user
+
+TODO: function to process each frame within the ObjectSet
\ No newline at end of file
diff --git a/target/classes/README.md b/target/classes/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c93df4abbe8779abb9ad11834d608762c273d314
--- /dev/null
+++ b/target/classes/README.md
@@ -0,0 +1,15 @@
+
+# Entry into System
+
+Things that are true:
+1. A student should be able to build the system, then press run, then open a localhost and see the video and the point cloud of each object
+2. A student should also be able to choose between different object and get information (need interactive display)
+3. The entry needs to do the entire workflow
+    - get keyframes and featurepoints
+    - get objects from keyframes
+    - start object detection
+    - finish object detection and update database
+    - ping GUI server
+    - GUI server pulls information and displays point cloud to user
+
+TODO: function to process each frame within the ObjectSet
\ No newline at end of file
diff --git a/target/classes/application 2.properties b/target/classes/application 2.properties
new file mode 100644
index 0000000000000000000000000000000000000000..4a5c2635a3e493971d146497da0075134f6914fa
--- /dev/null
+++ b/target/classes/application 2.properties	
@@ -0,0 +1,2 @@
+server.port = 5555
+#spring.data.mongodb.uri = mongodb+srv://zanem:<YXQiSFkSVqxPTs3M>@cluster0.axhv9kg.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0
\ No newline at end of file
diff --git a/target/classes/application.properties b/target/classes/application.properties
new file mode 100644
index 0000000000000000000000000000000000000000..4a5c2635a3e493971d146497da0075134f6914fa
--- /dev/null
+++ b/target/classes/application.properties
@@ -0,0 +1,2 @@
+server.port = 5555
+#spring.data.mongodb.uri = mongodb+srv://zanem:<YXQiSFkSVqxPTs3M>@cluster0.axhv9kg.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0
\ No newline at end of file
diff --git a/target/classes/database/MongoDBInteraction.class b/target/classes/database/MongoDBInteraction.class
new file mode 100644
index 0000000000000000000000000000000000000000..ad1989ee5cd63799f39e089923fb2792fe1c2f8c
Binary files /dev/null and b/target/classes/database/MongoDBInteraction.class differ
diff --git a/target/classes/extractedPoints 2.csv b/target/classes/extractedPoints 2.csv
new file mode 100644
index 0000000000000000000000000000000000000000..482821170b96860c836ae47d6f7624d9469d8fb5
--- /dev/null
+++ b/target/classes/extractedPoints 2.csv	
@@ -0,0 +1,365 @@
+-0.06900241,-0.3507448,1.033868
+-0.5094872,-0.335972,1.037024
+-0.0517595,-0.3194826,0.964794
+-0.26819,-0.2832867,0.93624
+-0.451066,-0.2754324,0.9582117
+-0.02466401,-0.2934302,1.022113
+0.4340152,-0.2927349,1.012656
+-0.4700845,-0.2324494,1.027293
+0.05616835,-0.2302022,1.02122
+0.3103633,-0.2405539,1.076906
+0.3468663,-0.2287515,1.026217
+-0.2542701,-0.1819791,0.9472755
+0.2602769,-0.2096001,1.085634
+0.4181629,-0.1918874,1.018657
+0.5108834,-0.1945888,1.10052
+0.1607228,-0.1786381,1.092534
+0.1154751,-0.1575818,1.033309
+0.3628199,-0.1240209,1.042551
+0.3392987,-0.1220983,1.065156
+0.09428331,-0.09280027,1.005206
+-0.4141278,-0.08583868,1.030251
+0.18329,-0.09223963,0.997163
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diff --git a/target/classes/extractedPoints.csv b/target/classes/extractedPoints.csv
new file mode 100644
index 0000000000000000000000000000000000000000..482821170b96860c836ae47d6f7624d9469d8fb5
--- /dev/null
+++ b/target/classes/extractedPoints.csv
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diff --git a/target/classes/object_detection/ObjectDetector 2.class b/target/classes/object_detection/ObjectDetector 2.class
new file mode 100644
index 0000000000000000000000000000000000000000..c9c367cf6a2a479ed4cd9cf9e0eab30be340c575
Binary files /dev/null and b/target/classes/object_detection/ObjectDetector 2.class differ
diff --git a/target/classes/object_detection/ObjectDetector.class b/target/classes/object_detection/ObjectDetector.class
new file mode 100644
index 0000000000000000000000000000000000000000..c9c367cf6a2a479ed4cd9cf9e0eab30be340c575
Binary files /dev/null and b/target/classes/object_detection/ObjectDetector.class differ
diff --git a/target/classes/object_detection/layout 2.md b/target/classes/object_detection/layout 2.md
new file mode 100644
index 0000000000000000000000000000000000000000..e20177dae76513b4e6962c626a942c14f14e04bf
--- /dev/null
+++ b/target/classes/object_detection/layout 2.md	
@@ -0,0 +1,20 @@
+
+Point: single feature
+- modify x,y,z coordinates
+- pointer to rep(s)
+
+PointSet: a single set of points that constitutes an object
+- made of a set of points, and some k number of object reps
+- object reps are chosen heuristically
+  - current ideas are to get middle most points, or corner most points as rep
+- also update reps when adding points to a PointSet
+
+ObjectSet: group of objects <--> to/from database
+- makeObject > instantiate HashSet of points
+- find-set > return list of k reps
+- union > combine two sets
+- union-find > find and union together
+
+ObjectMart: disjoint set operations, that gets coordinates from source
+- just a main function?
+- getObject > get new set of coordinates, make-set on them, try union-find
diff --git a/target/classes/object_detection/layout.md b/target/classes/object_detection/layout.md
new file mode 100644
index 0000000000000000000000000000000000000000..e20177dae76513b4e6962c626a942c14f14e04bf
--- /dev/null
+++ b/target/classes/object_detection/layout.md
@@ -0,0 +1,20 @@
+
+Point: single feature
+- modify x,y,z coordinates
+- pointer to rep(s)
+
+PointSet: a single set of points that constitutes an object
+- made of a set of points, and some k number of object reps
+- object reps are chosen heuristically
+  - current ideas are to get middle most points, or corner most points as rep
+- also update reps when adding points to a PointSet
+
+ObjectSet: group of objects <--> to/from database
+- makeObject > instantiate HashSet of points
+- find-set > return list of k reps
+- union > combine two sets
+- union-find > find and union together
+
+ObjectMart: disjoint set operations, that gets coordinates from source
+- just a main function?
+- getObject > get new set of coordinates, make-set on them, try union-find
diff --git a/target/classes/object_detection/types/BoundingBox.class b/target/classes/object_detection/types/BoundingBox.class
new file mode 100644
index 0000000000000000000000000000000000000000..97d18f0abaa395a2058eb975da5c2a00f3f94d8b
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diff --git a/target/classes/object_detection/types/ObjectSet.class b/target/classes/object_detection/types/ObjectSet.class
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diff --git a/target/classes/object_detection/types/Point.class b/target/classes/object_detection/types/Point.class
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diff --git a/target/classes/object_detection/types/Point2D.class b/target/classes/object_detection/types/Point2D.class
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diff --git a/target/classes/object_detection/types/PointSet.class b/target/classes/object_detection/types/PointSet.class
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index 0000000000000000000000000000000000000000..789ad4f59bc1c90e45a4a5613f954cd3d70aeeca
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diff --git a/target/classes/templates/html/index.html b/target/classes/templates/html/index.html
new file mode 100644
index 0000000000000000000000000000000000000000..ad4a36d45fdd57432ac830eb245a9ac8de8b3a45
--- /dev/null
+++ b/target/classes/templates/html/index.html
@@ -0,0 +1,30 @@
+<!DOCTYPE html>
+<html lang="en">
+
+<head>
+    <meta charset="UTF-8">
+    <title>VSlam</title>
+    <link rel="stylesheet" href="../style/main.css">
+    <!-- Include three.js -->
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r128/three.min.js"></script>
+</head>
+
+<body>
+    <p>Visual Simultaneous Localization and Mapping (VSLAM) is the process of taking camera feed, as well as its position, and building a map of the current local world, specifically using visual input. This project uses this process, and builds upon it by also tracking objects within a frame. In this comes two problems: object detection, and then subsequent mapping and tracking of objects within a 3D space. For more information go <a href="https://agile.bu.edu/gitlab/ec504/ec504_projects/group8/-/blob/master/README.md?ref_type=heads">here</a></p>
+    <h3>Press the button below to start the workflow and view the output</h3>
+    <input id="process" type="button" value="Start Workflow" onClick="startWorkflow();"/>
+    <div id="loading"></div>
+
+    <div class="container" id="resultContainer">
+        <div class="objects-container" id="objectsContainer">
+            <h4 style="margin: 0;">Select An Object To View Point Cloud With That Object Highlighted</h4>
+            <p style="margin: 0;"><em>point cloud can be manipulated through rotate and zoom</em></p>
+            <!-- Placeholder for Object List-->
+        </div>
+    </div>
+    <!-- <input id="drawPC" type="button" value="Show Point Cloud" onclick="drawPointCloud();" /> -->
+    <script src="../js/pointCloud.js"></script>
+    <script src="../js/app.js"></script>
+</body>
+
+</html>
diff --git a/target/classes/templates/js/app.js b/target/classes/templates/js/app.js
new file mode 100644
index 0000000000000000000000000000000000000000..2ac1825de39da991bfba1b760d4678512b9a04f1
--- /dev/null
+++ b/target/classes/templates/js/app.js
@@ -0,0 +1,71 @@
+async function fetchImageAndObjects() {
+    try {
+        const response = await fetch('http://127.0.0.1:5555/api/getObjects');
+        if (!response.ok) {
+            throw new Error('Failed to fetch image and objects');
+        }
+        const data = await response.json();
+
+        displayImageAndObjects(data.objects);
+    } catch (error) {
+        console.error(error);
+    }
+}
+
+function displayImageAndObjects(objects) {
+    const objectsContainer = document.getElementById('objectsContainer');
+    const container = document.getElementById('resultContainer');
+
+    // Create a list for objects
+    const objectsList = document.createElement('ul');
+    objects.forEach(object => {
+        const objectButton = document.createElement('button');
+        objectButton.textContent = object;
+        // Add event listener to each button
+        objectButton.addEventListener('click', () => {
+            // You can define what happens when the button is clicked
+            drawPointCloud(object);
+        });
+        const objectItem = document.createElement('li');
+        objectItem.appendChild(objectButton);
+        objectsList.appendChild(objectItem);
+    });
+
+    // Append objects list to the objects container
+    objectsContainer.appendChild(objectsList);
+
+    container.style.visibility = "visible";
+}
+
+
+// selecting loading div
+const loader = document.querySelector("#loading");
+
+// showing loading
+function displayLoading() {
+    loader.classList.add("display");
+}
+
+// hiding loading 
+function hideLoading() {
+    loader.classList.remove("display");
+}
+
+async function startWorkflow(){
+    const startButton = document.getElementById("process");
+    startButton.style.display = "none";
+    displayLoading();
+    try {
+        const response = await fetch('http://127.0.0.1:5555/runProcess');
+        if (!response.ok) {
+            throw new Error('Failed to fetch image and objects');
+        }
+        const data = await response;
+        console.log(data);
+        hideLoading();
+    } catch (error) {
+        console.error(error);
+    }
+    fetchImageAndObjects();
+    
+}
diff --git a/target/classes/templates/js/pointCloud.js b/target/classes/templates/js/pointCloud.js
new file mode 100644
index 0000000000000000000000000000000000000000..308687971ada84925dc77d653afae1c687e5ab10
--- /dev/null
+++ b/target/classes/templates/js/pointCloud.js
@@ -0,0 +1,139 @@
+async function drawPointCloud(object) {
+  await fetch('http://127.0.0.1:5555/getJSON')
+    .then(response => response.json())
+    .then(responseText => {
+      let pointCloudData = parseJSONToPointCloud(responseText, object);
+
+      // Use three.js to render the point cloud
+      let scene = new THREE.Scene();
+      let camera = new THREE.PerspectiveCamera(75, window.innerWidth / window.innerHeight, 0.1, 1000);
+      let renderer = new THREE.WebGLRenderer();
+      renderer.setSize(window.innerWidth, window.innerHeight);
+      document.body.appendChild(renderer.domElement);
+
+      // Create a buffer geometry and add the point cloud data
+      let geometry = new THREE.BufferGeometry();
+      geometry.setAttribute('position', new THREE.Float32BufferAttribute(new Float32Array(pointCloudData.positions), 3));
+      geometry.setAttribute('color', new THREE.Float32BufferAttribute(new Float32Array(pointCloudData.colors), 3));
+
+      let material = new THREE.PointsMaterial({ vertexColors: true, size: 0.005 });
+
+      let pointCloud = new THREE.Points(geometry, material);
+      scene.add(pointCloud);
+
+      camera.position.z = 2;
+
+      let angleX = 0;
+      let angleY = 0;
+
+      // Handle user interaction for rotation
+      let isDragging = false;
+      let previousMousePosition = {
+        x: 0,
+        y: 0
+      };
+
+      // Add event listeners to renderer's DOM element
+      renderer.domElement.addEventListener("mousedown", (event) => {
+        isDragging = true;
+        previousMousePosition = {
+          x: event.clientX,
+          y: event.clientY
+        };
+      });
+
+      renderer.domElement.addEventListener("mousemove", (event) => {
+        if (isDragging) {
+          let deltaX = event.clientX - previousMousePosition.x;
+          let deltaY = event.clientY - previousMousePosition.y;
+
+          angleY += deltaX * 0.01;
+          angleX += deltaY * 0.01;
+
+          pointCloud.rotation.y = angleY;
+          pointCloud.rotation.x = angleX;
+
+          previousMousePosition = {
+            x: event.clientX,
+            y: event.clientY
+          };
+
+          renderer.render(scene, camera);
+        }
+      });
+
+      renderer.domElement.addEventListener("mouseup", () => {
+        isDragging = false;
+      });
+
+      let zoomFactor = 1; // Initial zoom level
+
+      const zoomSensitivity = 0.01; // Adjust zoom sensitivity as needed
+
+      renderer.domElement.addEventListener("wheel", (event) => {
+        event.preventDefault();
+
+        zoomFactor += event.deltaY * zoomSensitivity;
+        zoomFactor = Math.max(0.1, zoomFactor); // Enforce minimum zoom level
+        camera.position.z = camera.initialPosition.z / zoomFactor;
+        renderer.render(scene, camera);
+      });
+
+      camera.initialPosition = { z: camera.position.z }; // Store initial position
+
+      function animate() {
+        requestAnimationFrame(animate);
+        renderer.render(scene, camera);
+      }
+
+      animate();
+
+      function parseJSONToPointCloud(jsonObject, target) {
+        // Initialize point cloud data
+        let positions = [];
+        let colors = [];
+      
+        // Check if the object name exists in the JSON
+        if (target in jsonObject || target == null) {
+          
+          for (let objectKey in jsonObject) {
+            let object = jsonObject[objectKey]['pset'];
+
+            // Loop through each coordinate in the object
+            for (let i = 0; i < object.length; i++) {
+              let coordinate = object[i];
+              
+              // Extract x, y, z values
+              let x = coordinate['x'];
+              let y = coordinate['y'];
+              let z = coordinate['z'];
+              let r,g,b;
+              
+              if(objectKey == target){
+                console.log(target);
+                r = 1; // Red component
+                g = 0; // Green component
+                b = 0; // Blue component
+              } else {
+                r = 1;
+                g = 1;
+                b = 1;
+              }
+
+              // Push to positions list
+              positions.push(x, y, z );
+              colors.push(r,g,b);
+            }
+          }
+
+        } else {
+          console.error(`Object '${object}' not found in JSON.`);
+        }
+      
+        return { positions: positions, colors: colors };
+      }
+    })
+    .catch(error => {
+      console.error('Error loading JSON:', error);
+    });
+}
\ No newline at end of file
diff --git a/target/classes/templates/style/main.css b/target/classes/templates/style/main.css
new file mode 100644
index 0000000000000000000000000000000000000000..24a5bdcb31b5da8e72e871c379d69c6d6eaf3066
--- /dev/null
+++ b/target/classes/templates/style/main.css
@@ -0,0 +1,72 @@
+html {
+  height: 100%;
+}
+
+body {
+  margin: 10px;
+}
+canvas {
+  display: block;
+}
+
+body {
+  font-family: Arial, sans-serif;
+  margin: 20px;
+}
+
+#resultContainer
+{
+  visibility: hidden;
+}
+
+.container {
+  display: flex;
+  justify-content: space-between;
+}
+
+.image-container {
+  flex: 1;
+  margin-right: 20px;
+}
+
+.objects-container {
+  flex: 1;
+}
+
+img {
+  max-width: 100%;
+  height: auto;
+}
+
+ul {
+  list-style-type: none;
+  padding-left: 0;
+}
+
+li {
+  margin-bottom: 5px;
+}
+
+/* creating css loader */
+
+#loading {
+  width: 2rem;
+  height: 2rem;
+  border: 5px solid #f3f3f3;
+  border-top: 6px solid #9c41f2;
+  border-radius: 100%;
+  margin: auto;
+  visibility: hidden;
+  animation: spin 1s infinite linear;
+}
+#loading.display {
+  visibility: visible;
+}
+@keyframes spin {
+  from {
+      transform: rotate(0deg);
+  }
+  to {
+      transform: rotate(360deg);
+  }
+}
diff --git a/target/classes/top/BackendJava 2.class b/target/classes/top/BackendJava 2.class
new file mode 100644
index 0000000000000000000000000000000000000000..bf825e3741abf576b6a5eda3b329f317bd553a9a
Binary files /dev/null and b/target/classes/top/BackendJava 2.class differ
diff --git a/target/classes/top/BackendJava$BackendService 2.class b/target/classes/top/BackendJava$BackendService 2.class
new file mode 100644
index 0000000000000000000000000000000000000000..dc2763604dc33173b2e6062cefd3460fb8390fbb
Binary files /dev/null and b/target/classes/top/BackendJava$BackendService 2.class differ
diff --git a/target/classes/top/BackendJava$BackendService.class b/target/classes/top/BackendJava$BackendService.class
new file mode 100644
index 0000000000000000000000000000000000000000..dc2763604dc33173b2e6062cefd3460fb8390fbb
Binary files /dev/null and b/target/classes/top/BackendJava$BackendService.class differ
diff --git a/target/classes/top/BackendJava$ObjectSetController 2.class b/target/classes/top/BackendJava$ObjectSetController 2.class
new file mode 100644
index 0000000000000000000000000000000000000000..e57c8bdc8e868e62aebf806ca04bf73f7c3cf38e
Binary files /dev/null and b/target/classes/top/BackendJava$ObjectSetController 2.class differ
diff --git a/target/classes/top/BackendJava$ObjectSetController.class b/target/classes/top/BackendJava$ObjectSetController.class
new file mode 100644
index 0000000000000000000000000000000000000000..e57c8bdc8e868e62aebf806ca04bf73f7c3cf38e
Binary files /dev/null and b/target/classes/top/BackendJava$ObjectSetController.class differ
diff --git a/target/classes/top/BackendJava$WebMvcConfig 2.class b/target/classes/top/BackendJava$WebMvcConfig 2.class
new file mode 100644
index 0000000000000000000000000000000000000000..fd34d8c5fa7f0eda5e246d7ac8f2b395d51091f3
Binary files /dev/null and b/target/classes/top/BackendJava$WebMvcConfig 2.class differ
diff --git a/target/classes/top/BackendJava$WebMvcConfig.class b/target/classes/top/BackendJava$WebMvcConfig.class
new file mode 100644
index 0000000000000000000000000000000000000000..fd34d8c5fa7f0eda5e246d7ac8f2b395d51091f3
Binary files /dev/null and b/target/classes/top/BackendJava$WebMvcConfig.class differ
diff --git a/target/classes/top/BackendJava.class b/target/classes/top/BackendJava.class
new file mode 100644
index 0000000000000000000000000000000000000000..bf825e3741abf576b6a5eda3b329f317bd553a9a
Binary files /dev/null and b/target/classes/top/BackendJava.class differ
diff --git a/target/classes/vslam/.DS_Store b/target/classes/vslam/.DS_Store
new file mode 100644
index 0000000000000000000000000000000000000000..2e11003f50bd8ea5dfa39826fd8eb50111ba0a94
Binary files /dev/null and b/target/classes/vslam/.DS_Store differ
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0003.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0003.csv
new file mode 100644
index 0000000000000000000000000000000000000000..056a5a481db43a670686bb63678f4e4fed5de8c9
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0003.csv
@@ -0,0 +1,15 @@
+Class,Confidence,X,Y,Width,Height
+chair,0.993455,49,263,216,217
+bottle,0.943588,374,139,20,54
+bottle,0.914840,202,40,26,74
+bottle,0.900759,177,35,26,72
+bottle,0.880150,348,124,20,70
+chair,0.863159,392,234,151,200
+bottle,0.847367,398,147,16,41
+book,0.843019,261,212,67,39
+bottle,0.777080,301,33,27,81
+book,0.741183,198,146,23,73
+cup,0.657321,543,203,22,27
+book,0.614862,214,146,24,73
+book,0.594223,232,147,15,71
+book,0.568934,186,146,20,73
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0004.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0004.csv
new file mode 100644
index 0000000000000000000000000000000000000000..30375fbc12f97202b928ebb57a7bdb172441bbf4
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0004.csv
@@ -0,0 +1,14 @@
+Class,Confidence,X,Y,Width,Height
+chair,0.989348,55,264,221,216
+bottle,0.972833,191,33,26,69
+bottle,0.915706,299,24,21,82
+bottle,0.913090,166,28,27,74
+bottle,0.910639,366,133,21,51
+book,0.910017,259,206,65,38
+chair,0.869248,393,216,138,205
+bottle,0.775094,388,139,15,40
+bottle,0.756660,288,25,14,80
+book,0.742734,180,144,24,69
+bottle,0.732562,340,121,20,66
+book,0.670628,193,140,34,74
+cup,0.655761,533,191,23,25
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0005.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0005.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a5953adcc99a2029e220292681b9da4a8bb7d599
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0005.csv
@@ -0,0 +1,15 @@
+Class,Confidence,X,Y,Width,Height
+chair,0.987287,115,273,198,206
+book,0.951032,294,210,58,38
+chair,0.945227,420,225,151,189
+bottle,0.933776,222,41,25,73
+cup,0.924748,551,193,22,25
+bottle,0.898357,318,33,21,77
+bottle,0.856866,194,37,24,70
+bottle,0.796510,384,137,23,50
+book,0.795472,231,147,25,72
+bottle,0.786705,408,143,14,40
+book,0.679131,217,148,21,72
+book,0.622862,254,147,16,71
+bottle,0.620367,312,33,15,76
+diningtable,0.505527,77,126,561,229
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0006.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0006.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e06a073135dc9ce4544c0e41637ce08a1c639fdb
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0006.csv
@@ -0,0 +1,14 @@
+Class,Confidence,X,Y,Width,Height
+chair,0.986703,195,240,177,234
+bottle,0.973417,270,3,25,75
+chair,0.964182,457,185,177,194
+cup,0.893079,594,160,23,25
+bottle,0.885799,357,-1,18,75
+bottle,0.853597,370,0,23,79
+book,0.795398,347,179,53,35
+bottle,0.787510,434,105,18,51
+book,0.762133,274,113,39,73
+bottle,0.711928,240,0,23,73
+bottle,0.602570,407,89,20,68
+book,0.566506,267,114,18,68
+book,0.529085,304,114,14,70
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0007.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0007.csv
new file mode 100644
index 0000000000000000000000000000000000000000..45114905023d106501f01be0bfc39a00fd19cc72
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0007.csv
@@ -0,0 +1,14 @@
+Class,Confidence,X,Y,Width,Height
+chair,0.980962,232,274,177,199
+bottle,0.974138,285,-1,29,86
+bottle,0.873482,455,104,22,56
+chair,0.870026,485,191,155,202
+bottle,0.839144,375,-2,22,76
+bottle,0.804067,393,0,25,78
+book,0.786843,378,190,57,38
+bottle,0.779136,252,2,24,77
+book,0.682283,297,119,29,83
+bottle,0.607538,426,91,30,74
+bottle,0.599189,472,107,12,46
+book,0.544751,318,119,20,81
+book,0.516700,286,123,17,67
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0008.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0008.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c0f107a5e17e249160ed220d7a76397283fe2919
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0008.csv
@@ -0,0 +1,12 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.956396,377,29,24,95
+bottle,0.951447,356,29,24,91
+bottle,0.934471,265,44,32,92
+bottle,0.785467,231,41,24,87
+chair,0.766622,247,362,191,117
+book,0.730273,374,240,69,40
+book,0.706878,316,170,20,85
+chair,0.683852,481,232,159,211
+bottle,0.637819,419,131,20,80
+book,0.633563,281,171,28,82
+book,0.509863,296,169,30,87
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0009.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0009.csv
new file mode 100644
index 0000000000000000000000000000000000000000..41a818fd58721e2848fbc2d5a3bdb9b54b146deb
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0009.csv
@@ -0,0 +1,11 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.989392,321,35,27,97
+bottle,0.979705,345,33,26,102
+bottle,0.936430,226,52,37,101
+book,0.931039,349,264,83,49
+cup,0.898504,582,196,29,30
+bottle,0.826991,413,160,22,61
+bottle,0.783535,182,44,30,102
+book,0.601428,246,194,67,91
+book,0.591419,285,189,26,97
+book,0.563663,233,201,27,91
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0010.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0010.csv
new file mode 100644
index 0000000000000000000000000000000000000000..05d0fd582d0b58e3aa9de541a55ed80977a09325
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0010.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.989190,298,-2,29,110
+bottle,0.979452,325,-1,30,114
+bottle,0.972495,195,23,44,117
+book,0.946781,343,250,99,62
+book,0.830862,231,185,57,116
+book,0.697451,257,179,49,110
+bottle,0.663523,139,14,40,108
+book,0.535742,215,195,32,111
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0011.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0011.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e4ba9a438efae215b80f1499a3615765d4f3dc17
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0011.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.987451,193,36,48,124
+bottle,0.977778,287,14,31,114
+bottle,0.975147,319,12,30,119
+book,0.958766,350,272,119,68
+book,0.830124,251,203,61,132
+book,0.776551,222,224,42,118
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0012.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0012.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3869913a12b6cf3db491e7cd8388ed4be15e3a48
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0012.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.992835,307,-1,31,115
+bottle,0.963762,223,2,51,143
+bottle,0.960663,340,0,34,116
+book,0.879273,378,259,125,68
+book,0.790902,276,186,68,150
+chair,0.687933,462,258,177,175
+scissors,0.569565,446,228,26,30
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0013.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0013.csv
new file mode 100644
index 0000000000000000000000000000000000000000..694560bfba54245199307e288a846aeebbbcfc1d
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0013.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.975009,388,2,37,124
+bottle,0.948660,355,3,34,116
+bottle,0.918266,299,19,45,132
+book,0.912712,424,261,123,65
+book,0.720314,329,201,49,131
+scissors,0.663079,484,230,25,28
+book,0.652247,351,187,53,144
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0014.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0014.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8f9c2601cc8e0755805e3ef22fb5d3ed0f693275
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0014.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.982068,405,27,35,107
+bottle,0.977063,374,26,33,103
+bottle,0.914378,348,40,29,119
+book,0.828439,442,260,103,56
+book,0.773026,379,196,34,124
+book,0.700694,365,212,29,112
+chair,0.649578,454,405,184,75
+book,0.578206,395,194,29,109
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0015.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0015.csv
new file mode 100644
index 0000000000000000000000000000000000000000..603c223a84b64bdbf37ee387cb6a97805ffbde13
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0015.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.956232,432,15,34,108
+bottle,0.833740,410,19,22,94
+book,0.722502,428,174,31,118
+book,0.641357,410,191,31,107
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0016.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0016.csv
new file mode 100644
index 0000000000000000000000000000000000000000..140647d3636ceab34c1e2053f769d7edd83bf46a
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0016.csv
@@ -0,0 +1,3 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.669045,423,21,33,103
+book,0.610651,418,178,31,111
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0017.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0017.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bc88505bf9bd169b6d6ca9b4c51402df66fb8f8e
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0017.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+chair,0.900084,476,272,164,204
+bottle,0.832877,383,15,20,86
+book,0.776666,389,161,38,117
+chair,0.514597,518,141,72,182
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0018.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0018.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b488e910a93438782cac206530565ba547b69d35
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0018.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+chair,0.912043,470,254,173,222
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0019.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0019.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1f72d25a42909714963b7e527873efdafe0525be
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0019.csv
@@ -0,0 +1,3 @@
+Class,Confidence,X,Y,Width,Height
+chair,0.926111,473,244,168,233
+chair,0.540201,488,133,50,95
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0020.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0020.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c42e95dc7a6d93f7a766eacfadaeac2553806ca9
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0020.csv
@@ -0,0 +1,3 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.902670,124,59,64,104
+chair,0.791025,475,223,169,253
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0021.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0021.csv
new file mode 100644
index 0000000000000000000000000000000000000000..73877f4cc362f9d244bb1f54caf12d90f4af5d30
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0021.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.925145,118,95,74,101
+tvmonitor,0.840341,198,96,69,119
+tvmonitor,0.759917,16,-1,82,41
+chair,0.709732,491,261,149,199
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0022.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0022.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7c8b5c3564ccd00d5d5f86f73d8872bc41be91a9
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0022.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.963351,102,89,81,107
+chair,0.734046,483,220,158,241
+chair,0.653522,462,124,36,66
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0023.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0023.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e772f0252777fbfe89e4ce17286759f5369adb47
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0023.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.788030,103,84,74,101
+sports ball,0.707112,297,436,86,43
+chair,0.654212,478,206,163,233
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0024.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0024.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ddab64e61e7befdca657180dd4b483aa2d61292e
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0024.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.904092,88,72,83,115
+tvmonitor,0.893758,200,70,63,116
+chair,0.821487,474,205,167,214
+chair,0.776018,449,107,40,66
+book,0.590785,142,191,92,36
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0025.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0025.csv
new file mode 100644
index 0000000000000000000000000000000000000000..607ce30264734ff22640f9ec9842548d58ee212f
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0025.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+tvmonitor,0.894847,196,70,49,119
+teddy bear,0.887727,54,79,85,122
+chair,0.839651,472,141,169,244
+bowl,0.724955,331,415,83,64
+chair,0.642681,-1,222,80,249
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0026.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0026.csv
new file mode 100644
index 0000000000000000000000000000000000000000..39313cd9b78996203954418fd07e4235724eb40b
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0026.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.956077,2,94,90,120
+chair,0.833243,445,152,180,228
+mouse,0.745801,77,270,38,21
+bowl,0.503701,319,421,83,59
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0027.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0027.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fcf21ac432e837ff06353059ac4f2f372192eb57
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0027.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.981039,85,261,38,22
+chair,0.929443,432,130,167,219
+keyboard,0.882909,99,205,46,55
+teddy bear,0.644617,1,92,66,125
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0028.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0028.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bebee24abef8d9b3d6c33484bfba3f2a6d513c5c
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0028.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.969620,104,287,39,22
+chair,0.865850,434,163,155,209
+keyboard,0.755108,102,231,70,51
+teddy bear,0.535001,-1,114,58,119
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0029.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0029.csv
new file mode 100644
index 0000000000000000000000000000000000000000..89b7782fe8cd05ef6121dd881f5d9a621eb39dd7
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0029.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.992161,190,274,36,21
+teddy bear,0.940446,14,101,99,119
+chair,0.867481,-1,283,167,197
+keyboard,0.862832,174,215,73,55
+book,0.592142,213,182,53,25
+chair,0.523947,499,153,136,208
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0030.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0030.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cbd86fb47f2ec02520082db4f694aa04d8cf0f2f
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0030.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.984722,239,244,35,21
+chair,0.970274,2,249,191,231
+teddy bear,0.680452,22,77,111,120
+chair,0.675579,539,118,99,209
+tvmonitor,0.549494,279,61,68,113
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0031.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0031.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a36bf84d49f9618e0daf5e031357bdd29329e874
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0031.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.984592,219,276,35,22
+keyboard,0.976352,173,220,85,52
+chair,0.917676,1,297,179,181
+chair,0.813675,507,118,100,202
+tvmonitor,0.757510,235,88,80,116
+teddy bear,0.717264,0,126,83,118
+tvmonitor,0.683940,159,85,39,74
+mouse,0.517078,128,192,24,11
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0032.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0032.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f8ff5211dee768e590c125a9e42547d037e3519b
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0032.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.992929,193,273,37,24
+keyboard,0.963473,131,220,104,51
+chair,0.869201,479,93,83,198
+tvmonitor,0.861603,99,74,54,90
+tvmonitor,0.770101,184,75,106,129
+keyboard,0.696463,81,158,53,32
+chair,0.645142,1,309,173,170
+book,0.554015,87,188,78,47
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0033.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0033.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d5fd5b3a2b65c8fe4a25cab0b7a9518ba3ee5685
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0033.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.991998,156,266,40,25
+mouse,0.880259,11,181,32,13
+keyboard,0.868838,79,205,121,58
+chair,0.852375,442,59,73,203
+tvmonitor,0.674498,129,47,121,143
+bottle,0.628045,211,176,28,66
+book,0.523286,28,173,82,45
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0034.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0034.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c8bdb4b916ff16dc6fc9319ad5c0404c1397be86
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0034.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.986446,147,318,45,31
+keyboard,0.971920,43,255,136,60
+tvmonitor,0.809121,0,93,39,98
+bottle,0.794709,200,217,30,68
+chair,0.744132,431,82,50,75
+tvmonitor,0.730553,91,82,144,162
+book,0.641214,52,197,85,44
+book,0.555855,2,237,73,49
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0035.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0035.csv
new file mode 100644
index 0000000000000000000000000000000000000000..56cdec749399c972df1b27284dd2cacd8573676d
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0035.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.976882,83,342,50,37
+tvmonitor,0.882500,4,81,178,178
+keyboard,0.871566,0,276,125,67
+bottle,0.866682,140,228,37,81
+chair,0.587082,383,88,36,79
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0036.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0036.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3dabc0044f38fb70f8c36d2c15b89a824cab6aa0
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0036.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.973950,52,373,52,42
+bottle,0.883179,108,254,36,81
+chair,0.663597,362,99,23,76
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0037.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0037.csv
new file mode 100644
index 0000000000000000000000000000000000000000..96248af70786c4b590084846a7051868c5a70e0a
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0037.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.993808,42,406,56,50
+bottle,0.980036,94,276,43,90
+tvmonitor,0.784195,-2,123,146,188
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0038.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0038.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1e27c7c9c136c6b316274a000dd80b0578dfd6dd
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0038.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.986761,66,275,47,89
+mouse,0.969147,15,416,59,56
+book,0.594914,118,212,110,53
+refrigerator,0.580960,322,1,106,95
+book,0.524686,195,201,104,61
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0039.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0039.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1a638adba228ce020aa25241d72dbdc84217a16d
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0039.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.986236,119,263,44,96
+mouse,0.972827,69,416,58,63
+tvmonitor,0.851170,-1,75,172,221
+keyboard,0.713300,1,344,93,82
+bowl,0.685524,272,182,56,37
+book,0.634608,259,189,134,66
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0040.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0040.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f4b6811d87d324937989dcbe73a64350b360c264
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0040.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.957150,185,257,46,106
+mouse,0.911916,128,417,62,63
+keyboard,0.812038,-1,323,160,96
+tvmonitor,0.775998,0,35,235,266
+cup,0.734770,354,187,62,41
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0041.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0041.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4754199f604a32265f3a87925f4049aee9f8a828
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0041.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.984894,-4,301,218,130
+tvmonitor,0.959247,26,30,279,280
+bottle,0.942808,246,267,45,115
+cup,0.679165,436,203,61,45
+mouse,0.663779,183,434,60,45
+book,0.648429,0,211,86,70
+book,0.531909,341,211,136,79
+book,0.509473,405,207,174,85
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0042.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0042.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a6dd5f6164b36bcf0588507a221bd44b755f76e0
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0042.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.976407,280,273,43,123
+keyboard,0.966962,1,300,235,149
+tvmonitor,0.952347,55,22,289,297
+book,0.806716,0,210,113,73
+book,0.633650,374,219,154,85
+cup,0.603149,482,211,69,49
+book,0.558447,459,225,176,86
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0043.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0043.csv
new file mode 100644
index 0000000000000000000000000000000000000000..67e553149bf37de4deb6d20cd23ac3bad6c72f1b
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0043.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.991141,4,309,256,152
+bottle,0.988393,305,283,43,125
+tvmonitor,0.970371,75,21,296,321
+book,0.778317,5,211,130,72
+bowl,0.548918,518,221,82,48
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0044.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0044.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7dcb9ee2974e903b12cc921ce5f4bd393d5341e3
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0044.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.987591,333,289,43,124
+keyboard,0.987158,18,305,266,158
+tvmonitor,0.973989,109,13,304,312
+book,0.895736,30,205,129,73
+book,0.712317,-1,243,74,92
+book,0.532727,448,228,173,125
+mouse,0.525104,0,393,14,55
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0045.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0045.csv
new file mode 100644
index 0000000000000000000000000000000000000000..81d4154b50dfcb863d28170cec74bf4e3729ba20
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0045.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.989469,373,288,49,127
+keyboard,0.978571,56,286,268,172
+book,0.950365,66,185,128,73
+book,0.756474,0,211,108,112
+book,0.580215,-1,273,114,74
+tvmonitor,0.570498,161,7,319,319
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0046.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0046.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e6b7a633fac640d36c1694a1bad29dace1815c45
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0046.csv
@@ -0,0 +1,12 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.994249,-1,161,53,24
+keyboard,0.992726,136,243,281,208
+keyboard,0.990268,-2,76,105,74
+bottle,0.982657,468,274,76,142
+mouse,0.925691,70,156,63,25
+tvmonitor,0.912880,251,-1,388,325
+book,0.904989,27,167,164,109
+tvmonitor,0.891693,33,0,98,92
+book,0.794541,153,143,128,73
+book,0.705981,57,231,135,54
+mouse,0.518463,79,320,49,50
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0047.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0047.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2e241329f425d6d60973c15e8f783e0b5b484a30
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0047.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.986461,108,155,50,23
+keyboard,0.956256,242,256,288,217
+tvmonitor,0.956031,367,-4,271,377
+book,0.931906,139,169,159,100
+book,0.857453,258,149,127,73
+mouse,0.856831,185,321,47,50
+tvmonitor,0.668790,152,-1,93,97
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0048.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0048.csv
new file mode 100644
index 0000000000000000000000000000000000000000..dba924887f79876464b677d5210a74831b08afcf
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0048.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.970629,161,179,48,23
+tvmonitor,0.932175,414,-5,225,377
+book,0.913494,307,176,123,73
+book,0.881489,190,194,154,101
+keyboard,0.847220,287,286,345,195
+tvmonitor,0.586018,203,1,101,121
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0049.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0049.csv
new file mode 100644
index 0000000000000000000000000000000000000000..58e94365638add60f8c81f7d0dfc7cb10493f035
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0049.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.996182,357,306,282,170
+keyboard,0.995689,217,118,99,69
+mouse,0.991718,224,195,48,22
+tvmonitor,0.937791,486,-3,153,375
+book,0.933482,256,215,156,95
+book,0.927526,374,196,131,75
+teddy bear,0.856052,-1,49,124,222
+chair,0.526166,-3,148,193,293
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0050.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0050.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5bf319c604ebe003bcca7cf17d7e06d9128e5597
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0050.csv
@@ -0,0 +1,10 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.997539,412,311,226,168
+keyboard,0.997217,214,141,107,68
+mouse,0.993241,243,221,47,23
+book,0.951588,288,228,160,106
+book,0.855667,400,203,115,77
+tvmonitor,0.827005,504,5,135,358
+mouse,0.770092,312,218,52,25
+tvmonitor,0.727272,257,12,107,143
+book,0.536002,318,295,133,47
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0051.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0051.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c4b9c2779aee96c781448349ffdedcd03caf1430
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0051.csv
@@ -0,0 +1,10 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.998304,182,151,125,66
+mouse,0.987546,241,230,46,24
+keyboard,0.986786,443,291,196,150
+tvmonitor,0.945330,493,5,145,311
+book,0.936693,305,225,152,102
+tvmonitor,0.928863,219,22,111,138
+book,0.828512,396,190,106,71
+mouse,0.664809,312,218,44,26
+chair,0.569753,-1,163,216,311
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0052.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0052.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0163e791900ebe3149ad91208ac9ad99d4cd317a
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0052.csv
@@ -0,0 +1,10 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.997656,151,154,135,58
+mouse,0.992243,238,226,42,28
+keyboard,0.991058,463,263,176,96
+tvmonitor,0.955044,169,17,125,135
+book,0.927136,314,203,151,112
+tvmonitor,0.927015,470,-4,170,276
+book,0.651802,387,167,93,64
+chair,0.625205,0,206,212,266
+mouse,0.571924,309,206,38,26
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0053.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0053.csv
new file mode 100644
index 0000000000000000000000000000000000000000..06c44e82f45673307e76074e2533d050e7f29289
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0053.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.997503,194,215,42,29
+keyboard,0.995452,76,148,151,54
+keyboard,0.995075,433,229,206,78
+tvmonitor,0.942724,416,-1,224,216
+book,0.926410,280,183,142,98
+tvmonitor,0.864124,76,4,155,131
+book,0.608683,261,128,100,58
+cell phone,0.504619,267,187,33,36
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0054.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0054.csv
new file mode 100644
index 0000000000000000000000000000000000000000..97cf2fe0c3ebc3fc4c16bc112763dc038c835a48
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0054.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.998064,233,222,43,33
+keyboard,0.996474,95,147,166,63
+keyboard,0.992272,503,241,137,76
+book,0.892637,337,189,150,108
+tvmonitor,0.892488,468,-2,172,221
+tvmonitor,0.731381,91,1,172,135
+book,0.594573,297,130,103,58
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0055.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0055.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1228443060e5afe91aea622dbbcaabd2d3b4cf1f
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0055.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.997529,183,272,51,44
+keyboard,0.995232,484,272,154,80
+keyboard,0.989084,7,191,207,65
+tvmonitor,0.892294,0,-1,208,170
+tvmonitor,0.839755,436,0,209,225
+book,0.794489,306,231,161,129
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0056.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0056.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6bad592b6927f86d2622b29f3b67739a34f49d94
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0056.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.997361,126,309,52,53
+keyboard,0.992701,446,275,191,90
+keyboard,0.991297,1,232,143,61
+tvmonitor,0.963257,387,0,253,214
+tvmonitor,0.862737,-1,16,142,190
+book,0.677432,273,250,152,133
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0057.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0057.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1ad1148afbac5b9944b00a350f408f7493cdae2c
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0057.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.997904,49,329,66,66
+keyboard,0.980856,0,237,76,71
+keyboard,0.977580,415,265,226,122
+tvmonitor,0.926325,343,-2,300,196
+tvmonitor,0.720451,0,0,64,229
+book,0.652749,243,257,148,157
+orange,0.602857,481,415,69,55
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0058.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0058.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7a0ecc437177259fcf5f9df943f13e78540b25f7
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0058.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.998642,24,335,79,74
+keyboard,0.963408,0,218,72,83
+keyboard,0.961810,443,333,197,114
+tvmonitor,0.956909,377,-2,262,275
+book,0.787308,273,284,141,179
+tvmonitor,0.721229,1,0,67,219
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0059.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0059.csv
new file mode 100644
index 0000000000000000000000000000000000000000..56bfe1ad86066a5a4137ee662e8928546756a12d
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0059.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.990767,119,307,78,69
+keyboard,0.932575,0,128,193,141
+tvmonitor,0.776644,-2,-1,203,163
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0060.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0060.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bd8544564a0d5fc5972a6dc8cc6b5b8ef7b6e8e5
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0060.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.966170,187,292,78,65
+tvmonitor,0.911748,64,-2,228,136
+keyboard,0.845111,25,113,245,130
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0061.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0061.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7126e117d332869917911aaceeede403715e435a
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0061.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.997089,274,310,79,60
+keyboard,0.995719,140,115,221,151
+tvmonitor,0.866134,188,-2,245,161
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0062.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0062.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f7bbefa6b1f68310c08f1d68d2ac6ac29ec1da41
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0062.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.976677,211,111,230,164
+mouse,0.966137,351,327,80,61
+tvmonitor,0.525676,279,-3,273,169
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0063.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0063.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6bd3d4146fdb150056c7c5d6dfe040bd262a955a
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0063.csv
@@ -0,0 +1,3 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.841019,294,125,234,188
+tvmonitor,0.698901,365,1,272,271
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0064.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0064.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6bd0f82e111476005f4a18637a786ff57a7ebed1
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0064.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.841598,496,423,98,57
+tvmonitor,0.770743,433,-2,207,291
+teddy bear,0.646202,0,-6,251,493
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0065.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0065.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0b252df315fc24a2d3fc1e5eee865776d933d386
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0065.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.969177,426,177,212,243
+teddy bear,0.808670,8,4,344,464
+tvmonitor,0.753566,506,-3,135,277
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0066.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0066.csv
new file mode 100644
index 0000000000000000000000000000000000000000..09b7629e22c2c9e581f79efd8d75a96e1fd19a72
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0066.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.950157,4,8,351,457
+keyboard,0.882067,449,177,191,291
+tvmonitor,0.652187,527,-1,112,221
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0067.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0067.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8e41fc81561e142292df729110764275a8e6cf32
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0067.csv
@@ -0,0 +1,3 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.986617,7,-8,348,482
+keyboard,0.956846,494,165,148,195
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0068.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0068.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c3f05f23049ee9b32bb05089de86fd7b95c84b8e
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0068.csv
@@ -0,0 +1,3 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.979545,6,-6,353,481
+keyboard,0.853897,523,168,117,180
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0069.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0069.csv
new file mode 100644
index 0000000000000000000000000000000000000000..67bb2395ab7b2d336730400fc1dcccd3b4e52ddc
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0069.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.979980,14,-12,390,497
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0070.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0070.csv
new file mode 100644
index 0000000000000000000000000000000000000000..34767e3cb7ca257d2b265c9e73097d43971057ad
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0070.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.959864,18,-15,391,508
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0071.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0071.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3b5117f1d49d4c5d50e8162cdd515c88f0e7fbbe
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0071.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.964417,13,-17,406,501
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0072.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0072.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6a79750ba1496370d929a4c477c7367635107a46
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0072.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.963384,12,-9,410,490
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0073.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0073.csv
new file mode 100644
index 0000000000000000000000000000000000000000..427889ba6db7835124377eb56ff58da3dd06f1f9
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0073.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.897331,53,-18,395,501
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0074.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0074.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3af8179582f511f8d7006356fa6bce4b5a7fd625
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0074.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.907018,57,-17,397,502
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0075.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0075.csv
new file mode 100644
index 0000000000000000000000000000000000000000..43eb2fbdb8adb6669748435e67a84e97016eea75
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0075.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.891879,104,-21,363,507
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0076.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0076.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e2be25476a7146a99dc45df0d0cec2a8661e6acc
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0076.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.976047,158,-4,392,483
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0077.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0077.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a53ec1f9096aad7904abcb2b4215280945b60a30
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0077.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.919677,193,18,394,454
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0078.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0078.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6bf0fb6eca5c2fa315fa671bc8687dfeda420535
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0078.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.880899,204,45,384,421
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0079.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0079.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d7610205de7d60c87e0a705b780fea9c86faaef7
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0079.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.949446,211,70,375,395
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0080.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0080.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2b85834a9a5c0a87f1b8f9098695ccc103fb91ba
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0080.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.943422,220,102,340,370
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0081.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0081.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d2dc2186d48bf1000b3c5e23247c24f1474967af
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0081.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.964526,210,102,334,370
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0082.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0082.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2538406c76912cf339679dcfc521c2a9070f0a9a
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0082.csv
@@ -0,0 +1,2 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.964247,218,99,337,370
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0083.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0083.csv
new file mode 100644
index 0000000000000000000000000000000000000000..854cc88592081a0cecabac8690631fa0988e0a95
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0083.csv
@@ -0,0 +1,3 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.911169,258,112,303,348
+keyboard,0.603885,593,192,47,63
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0084.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0084.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d22c3a137808c633fcc1fa48ebfc41cbe196aae2
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0084.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.982134,542,175,99,66
+teddy bear,0.890726,259,88,280,354
+tvmonitor,0.714671,581,10,59,170
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0085.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0085.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b6e90285aa0df9eef12ba20e678d2958aa398805
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0085.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.988527,487,152,152,83
+teddy bear,0.951176,248,95,257,274
+tvmonitor,0.924297,513,11,127,160
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0086.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0086.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f36987988211d421ed2a0a4bdf3e231fd088bd73
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0086.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.995563,433,150,167,55
+mouse,0.967109,596,214,35,24
+teddy bear,0.945592,223,108,259,254
+tvmonitor,0.841869,447,3,190,169
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0087.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0087.csv
new file mode 100644
index 0000000000000000000000000000000000000000..985fdae43a912c6aaff94077f492b510122e47b8
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0087.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.997224,398,158,152,46
+tvmonitor,0.956237,405,31,159,121
+mouse,0.895689,560,209,29,24
+teddy bear,0.787820,217,112,252,264
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0088.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0088.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b5b7393e71b5207ad52b0e6fe14d29d2697e6941
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0088.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.997284,385,172,138,36
+tvmonitor,0.969575,385,46,144,121
+mouse,0.944910,542,216,25,21
+teddy bear,0.822062,214,145,249,241
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0089.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0089.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7c3e7855ed90bd6a7670bd7e6c31eda462caae7b
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0089.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.995163,355,194,130,33
+tvmonitor,0.948096,349,70,138,107
+mouse,0.946513,511,230,21,20
+chair,0.928286,211,259,241,218
+teddy bear,0.703841,207,163,243,218
+mouse,0.503965,551,212,25,21
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0090.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0090.csv
new file mode 100644
index 0000000000000000000000000000000000000000..352713e6ec1c76266e04fc01c7b958baf90e892c
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0090.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.995661,318,222,132,33
+tvmonitor,0.987442,299,96,137,120
+book,0.886623,556,217,82,46
+mouse,0.865009,478,251,22,20
+teddy bear,0.812260,185,225,263,236
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0091.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0091.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8bfadec2715b211839539f68a12aab4e871ad45e
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0091.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.990059,298,213,136,34
+tvmonitor,0.912814,278,92,145,109
+mouse,0.885176,462,241,23,20
+chair,0.851148,169,308,252,171
+book,0.501083,496,184,141,72
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0092.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0092.csv
new file mode 100644
index 0000000000000000000000000000000000000000..32e460a81bc197f0f623f1bedd3abf8f743b7cce
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0092.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.988408,291,198,129,39
+chair,0.955053,166,302,250,173
+tvmonitor,0.827685,267,77,148,118
+book,0.571689,486,181,141,64
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0093.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0093.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c7366edc7600b9b90fb6ec0b6a281b8cb7447f77
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0093.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.990000,283,197,132,39
+tvmonitor,0.980704,260,74,137,116
+tvmonitor,0.739980,537,32,103,153
+mouse,0.739738,444,227,21,23
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0094.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0094.csv
new file mode 100644
index 0000000000000000000000000000000000000000..17923a729d61feb4c10d2f73ae5a0abaa5d1b4cb
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0094.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.994190,243,199,132,36
+tvmonitor,0.986626,211,75,148,118
+mouse,0.912320,405,225,22,20
+tvmonitor,0.838532,494,36,144,135
+book,0.826020,470,190,93,46
+teddy bear,0.712100,116,215,275,250
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0095.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0095.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ad8177426db25521f2d8d2640e056d25459b0115
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0095.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.999044,172,174,146,41
+tvmonitor,0.966439,124,41,168,134
+mouse,0.919518,349,198,27,21
+book,0.872374,402,153,102,43
+tvmonitor,0.811700,418,1,169,135
+teddy bear,0.749336,63,200,302,268
+keyboard,0.725887,484,146,116,42
+bottle,0.582120,569,90,27,53
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0096.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0096.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9fc3f0d62dac10bcd3db27cb0841f6ea75bcacd4
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0096.csv
@@ -0,0 +1,12 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.997820,147,181,154,57
+mouse,0.980764,332,203,29,23
+keyboard,0.961634,467,133,107,49
+tvmonitor,0.936243,87,47,179,148
+book,0.930847,386,149,96,50
+tvmonitor,0.886054,392,-2,162,136
+bottle,0.821694,541,77,23,58
+mouse,0.748815,579,139,35,18
+book,0.746661,338,136,84,39
+chair,0.706589,529,121,110,343
+teddy bear,0.647153,53,225,313,244
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0097.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0097.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7ec7d4c26fd01e7f50e0e95b34aebf5324abcbb0
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0097.csv
@@ -0,0 +1,13 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.995570,120,180,161,68
+mouse,0.987830,314,199,31,23
+keyboard,0.979041,445,125,107,47
+tvmonitor,0.962779,366,-1,154,129
+book,0.958160,369,142,93,50
+bottle,0.887575,515,66,23,56
+tvmonitor,0.875259,48,38,197,163
+book,0.691024,316,124,88,45
+mouse,0.630964,330,169,33,19
+chair,0.597831,522,226,117,219
+teddy bear,0.575661,26,231,329,219
+mouse,0.559132,559,125,30,18
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0098.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0098.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1d7d2080b18df953a085cc0c34b2e65e10e7fdb1
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0098.csv
@@ -0,0 +1,11 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.997698,93,166,174,75
+mouse,0.991263,297,185,34,23
+book,0.955696,348,122,99,50
+tvmonitor,0.941328,342,-1,147,113
+bottle,0.902354,488,43,22,60
+keyboard,0.893120,427,105,94,46
+tvmonitor,0.856400,5,12,221,184
+chair,0.822685,492,108,147,314
+book,0.660147,296,106,82,45
+teddy bear,0.629646,24,219,259,210
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0099.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0099.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5bce6e45c55d0f31b063eba9e2ae097ab278c62a
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0099.csv
@@ -0,0 +1,12 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.996960,97,154,170,90
+mouse,0.990371,301,173,33,21
+book,0.946725,343,107,96,54
+chair,0.915786,487,39,154,360
+tvmonitor,0.901429,-2,8,216,195
+bottle,0.893618,467,28,19,57
+tvmonitor,0.892278,327,0,137,97
+keyboard,0.844573,420,86,82,48
+teddy bear,0.690435,82,210,296,217
+mouse,0.663089,215,208,66,32
+mouse,0.568964,509,84,29,16
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0100.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0100.csv
new file mode 100644
index 0000000000000000000000000000000000000000..dd7d657a152697fd28d2e01cec108ad04a6b26c5
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0100.csv
@@ -0,0 +1,11 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.996251,96,147,170,98
+mouse,0.995156,298,161,36,22
+bottle,0.935691,437,13,18,60
+tvmonitor,0.929137,304,0,129,91
+chair,0.907215,468,53,172,293
+tvmonitor,0.878736,-1,0,206,194
+book,0.872986,332,94,92,49
+keyboard,0.852359,401,72,77,45
+teddy bear,0.651166,151,193,285,237
+mouse,0.579405,478,67,30,15
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0101.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0101.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d25b6c1903f67fcc23a8be4aa55751b52d7b056e
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0101.csv
@@ -0,0 +1,11 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.997536,99,130,165,110
+mouse,0.996214,297,138,37,21
+chair,0.979816,464,7,175,297
+book,0.861515,316,67,101,46
+tvmonitor,0.833843,-3,1,198,211
+tvmonitor,0.817126,278,-1,122,70
+mouse,0.601536,451,33,30,14
+teddy bear,0.587897,218,163,279,214
+keyboard,0.562098,380,39,72,45
+book,0.502167,318,94,97,33
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0102.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0102.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cd9dec13358f26531090646a24a3b9186287b9bc
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0102.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.997353,152,122,146,101
+mouse,0.989065,331,127,38,20
+tvmonitor,0.923724,304,-1,106,64
+book,0.874115,344,64,97,46
+tvmonitor,0.850173,22,-2,206,182
+keyboard,0.696262,402,35,63,40
+teddy bear,0.547217,324,142,263,200
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0103.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0103.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8163762205e8f2bd4656ea9f405007982362c765
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0103.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.992513,191,128,132,94
+mouse,0.988567,355,131,35,19
+tvmonitor,0.787498,316,-1,96,72
+bottle,0.705409,422,0,18,43
+mouse,0.689560,464,38,28,16
+teddy bear,0.570712,328,139,319,300
+tvmonitor,0.526028,73,2,178,183
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0104.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0104.csv
new file mode 100644
index 0000000000000000000000000000000000000000..01b2e614afcc75d5dac8365390adb364ddb2c4c4
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0104.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.993996,275,137,117,84
+mouse,0.983882,424,141,36,19
+tvmonitor,0.926945,387,-1,86,88
+tvmonitor,0.768773,184,0,146,183
+bottle,0.652326,482,8,19,50
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0105.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0105.csv
new file mode 100644
index 0000000000000000000000000000000000000000..66ccc53d0950c7f1c71866b557f324eb35499c5a
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0105.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.996592,338,154,110,89
+mouse,0.992854,477,157,39,18
+tvmonitor,0.916802,257,17,122,189
+tvmonitor,0.910868,423,0,81,105
+mouse,0.909910,558,70,25,15
+bottle,0.585695,511,26,20,47
+book,0.535185,471,100,89,37
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0106.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0106.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fe75e7b91e44df4a95e7efc1e4ac85584784fb0b
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0106.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.995654,398,145,108,91
+mouse,0.990071,531,148,39,18
+tvmonitor,0.828425,331,6,98,185
+mouse,0.826751,591,60,29,15
+tvmonitor,0.798658,466,-2,75,92
+book,0.656281,519,90,88,33
+keyboard,0.509139,420,111,53,38
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0107.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0107.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c79cebbb54a693e602a8f5cbeed9c59ada928e66
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0107.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+keyboard,0.987102,410,141,88,85
+mouse,0.978396,522,140,39,18
+tvmonitor,0.932645,348,6,78,183
+mouse,0.765684,564,58,26,14
+bottle,0.669386,521,15,21,48
+chair,0.622972,41,76,84,80
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0108.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0108.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0ad359640049d2255d7817a94ddc3f238c5453f6
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0108.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.966437,494,114,36,16
+keyboard,0.944315,402,116,68,80
+tvmonitor,0.925464,337,-1,70,165
+tvmonitor,0.703639,418,0,52,63
+mouse,0.675864,519,39,24,13
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0109.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0109.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2930515fefae15314ef5a2b59201ed970c38fb62
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0109.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.936371,456,92,34,16
+tvmonitor,0.684495,310,0,66,146
+bottle,0.670627,119,84,68,160
+keyboard,0.613848,388,100,51,70
+mouse,0.602097,458,21,22,14
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0110.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0110.csv
new file mode 100644
index 0000000000000000000000000000000000000000..de29f6a8b972d28bd6a43eb72a96decc26e799a4
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0110.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+bowl,0.901394,323,371,117,107
+mouse,0.882690,464,85,33,15
+bottle,0.712161,179,170,49,82
+chair,0.704787,64,15,87,101
+keyboard,0.604854,408,97,47,67
+bottle,0.602876,149,97,48,101
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0111.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0111.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9a316f3dfda401058315f01baa4302d7e082b534
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0111.csv
@@ -0,0 +1,10 @@
+Class,Confidence,X,Y,Width,Height
+chair,0.941823,10,35,89,111
+bowl,0.921416,311,367,114,111
+chair,0.851310,463,1,80,125
+bottle,0.800953,169,173,52,89
+mouse,0.781015,417,97,30,14
+keyboard,0.765873,375,109,46,56
+tvmonitor,0.740846,304,2,52,160
+cup,0.732113,14,185,40,44
+bowl,0.701947,0,230,55,33
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0112.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0112.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f3ab3012a659fdfbe19bc9e8a8276b04b0c752ed
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0112.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+bowl,0.872484,326,351,107,119
+chair,0.856789,-1,44,94,120
+chair,0.797391,437,11,80,113
+tvmonitor,0.580046,300,2,55,152
+teddy bear,0.535700,525,37,115,205
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0113.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0113.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9aa2842cacf392ac61adb3de08a9e95097a924d1
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0113.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+chair,0.952016,446,24,74,108
+keyboard,0.940411,383,120,53,48
+chair,0.923624,10,59,102,115
+bowl,0.918963,359,352,103,120
+mouse,0.892737,421,110,27,13
+bottle,0.848654,231,119,43,136
+tvmonitor,0.598462,324,15,58,142
+cup,0.517698,121,176,29,24
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0114.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0114.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0f71acf88de7673cb630087a819ad824d2e3c020
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0114.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.952780,239,113,55,139
+laptop,0.929003,314,15,129,150
+mouse,0.893135,405,102,28,13
+cup,0.861550,67,205,41,41
+chair,0.845010,1,71,89,105
+bowl,0.822241,379,342,103,98
+chair,0.738432,415,18,77,94
+bowl,0.563083,75,243,47,34
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0115.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0115.csv
new file mode 100644
index 0000000000000000000000000000000000000000..841d9deb899fefdce33b6eb3a5a1a92fe26e8b57
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0115.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+laptop,0.979908,243,51,133,134
+bottle,0.764694,194,149,54,125
+teddy bear,0.758541,430,45,145,140
+keyboard,0.650963,316,140,51,42
+chair,0.637017,328,47,76,82
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0116.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0116.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1c1f23ebfb557d5d2499b5f5c3a53588ce40c40a
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0116.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.886961,125,50,35,91
+chair,0.649584,327,19,65,67
+bottle,0.621302,225,99,47,122
+mouse,0.562381,337,91,23,13
+chair,0.556069,412,32,156,295
+teddy bear,0.548584,459,14,113,129
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0117.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0117.csv
new file mode 100644
index 0000000000000000000000000000000000000000..228d11961cff3aae64b9e9c136f66aaf33640059
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0117.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.913542,117,68,40,90
+bottle,0.846079,149,93,24,55
+teddy bear,0.654156,426,-1,129,118
+bottle,0.623591,81,0,34,43
+bottle,0.528616,105,0,38,39
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0118.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0118.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c0b9566c5de4a0321982a41e98166ab0cb1caf8c
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0118.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.887259,115,71,41,90
+bottle,0.762994,269,98,50,118
+teddy bear,0.744194,439,0,100,115
+bottle,0.592962,152,96,23,57
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0119.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0119.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8e247e94776e9929251f257b7d8aefb1076f5f2b
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0119.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+teddy bear,0.837201,441,38,80,101
+bottle,0.831190,290,126,50,115
+bottle,0.713512,120,107,45,95
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0120.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0120.csv
new file mode 100644
index 0000000000000000000000000000000000000000..23578db47acaa4918a5d664a3a3edbb1058eacea
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0120.csv
@@ -0,0 +1,11 @@
+Class,Confidence,X,Y,Width,Height
+cup,0.969409,174,267,31,40
+bottle,0.928067,149,34,33,70
+bottle,0.775592,176,154,29,56
+bottle,0.754805,203,156,22,51
+bottle,0.725005,352,154,40,109
+teddy bear,0.695578,472,76,85,97
+bowl,0.676720,212,292,42,33
+bottle,0.602451,123,34,39,74
+chair,0.552979,-3,261,151,147
+bottle,0.543496,226,160,21,52
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0121.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0121.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b21952b3549362fdc3597aa8978baf4b49882426
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0121.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.949800,350,111,38,109
+cup,0.922582,171,235,36,45
+knife,0.884717,103,254,56,33
+bottle,0.868802,83,0,52,77
+bottle,0.836064,143,117,34,64
+chair,0.625454,2,260,218,219
+bottle,0.615429,174,114,28,61
+teddy bear,0.597755,441,38,83,93
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0122.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0122.csv
new file mode 100644
index 0000000000000000000000000000000000000000..213910af413991c0af2f6a491beef5bfc938fa25
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0122.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.884274,373,114,34,111
+bottle,0.793660,158,127,33,64
+bottle,0.776791,187,123,25,62
+bottle,0.736872,94,7,46,81
+knife,0.712312,130,257,57,35
+bottle,0.700056,116,9,40,75
+chair,0.661728,3,265,241,208
+bottle,0.502302,148,111,25,78
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0123.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0123.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ce3ee70f46bb100c7aca48dc9e013088032dfc94
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0123.csv
@@ -0,0 +1,15 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.891865,374,102,32,106
+bottle,0.880272,85,-1,50,82
+bottle,0.843739,176,115,28,59
+bottle,0.808967,199,120,15,48
+bottle,0.792428,212,130,19,52
+bottle,0.782619,41,12,38,61
+book,0.740257,18,114,38,73
+cup,0.686684,217,222,31,41
+chair,0.674686,-1,237,250,239
+spoon,0.651309,143,243,52,32
+bottle,0.614934,20,9,43,77
+bottle,0.590446,139,111,34,71
+bottle,0.580967,155,118,31,61
+bottle,0.537435,0,-1,38,85
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0124.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0124.csv
new file mode 100644
index 0000000000000000000000000000000000000000..308969f5ecc06ff9887b006a60fd038a70a94c7d
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0124.csv
@@ -0,0 +1,10 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.929072,374,76,31,103
+chair,0.924973,4,227,251,247
+book,0.898446,0,105,27,75
+bowl,0.831694,280,216,40,28
+bottle,0.828486,162,111,26,47
+bottle,0.810163,197,114,21,48
+cup,0.771551,227,200,30,43
+bottle,0.702990,181,102,18,50
+bottle,0.651468,144,109,28,55
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0125.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0125.csv
new file mode 100644
index 0000000000000000000000000000000000000000..73d97656f4c7896169e02a57e25a09ab98f6df10
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0125.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.929553,321,96,34,98
+chair,0.816352,-4,286,220,193
+bottle,0.770832,96,142,30,54
+bottle,0.762161,131,146,26,50
+person,0.693264,557,1,66,69
+bottle,0.661111,113,136,26,50
+bottle,0.596342,74,141,36,60
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0126.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0126.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3a9fcea31550502489ab4cedaf5376c67de463b2
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0126.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.918341,286,64,37,106
+bottle,0.913501,76,130,33,55
+cup,0.840980,166,211,34,44
+spoon,0.744079,88,251,37,44
+bottle,0.683450,17,126,40,64
+person,0.665286,475,0,46,41
+bottle,0.636932,36,130,34,54
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0127.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0127.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cb851b830be86f1f65bf243604c4ebd71f82251e
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0127.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.986830,270,59,40,104
+cup,0.973837,168,220,36,47
+cup,0.899897,114,219,35,35
+bottle,0.786341,37,142,40,59
+spoon,0.637487,89,270,32,51
+bottle,0.585662,8,134,31,47
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0128.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0128.csv
new file mode 100644
index 0000000000000000000000000000000000000000..905e11422a5285f79dd2217313ac8afa65e98fb5
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0128.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.986147,215,47,43,118
+cup,0.975396,132,223,42,50
+bottle,0.872400,24,137,48,70
+cup,0.743198,67,230,40,38
+knife,0.675210,61,288,22,58
+cup,0.666992,76,158,39,41
+chair,0.500141,-1,345,123,134
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0129.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0129.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a5f1f6810956d657e68b05209d47f4da9cfdb470
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0129.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.989257,221,47,50,117
+cup,0.966823,88,247,41,39
+cup,0.960745,166,234,45,55
+bottle,0.863279,22,150,52,74
+knife,0.733612,103,310,11,66
+cup,0.592613,79,168,42,44
+chair,0.541943,-1,384,164,94
+person,0.531906,256,0,47,21
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0130.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0130.csv
new file mode 100644
index 0000000000000000000000000000000000000000..afc9ed261c66b8a85448c2770ffbe8ec6463f3e6
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0130.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.971135,202,36,54,125
+knife,0.944997,106,333,20,72
+cup,0.934203,79,263,47,41
+cup,0.861223,170,242,48,59
+cup,0.753204,51,179,47,45
+chair,0.544201,-1,417,177,62
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0131.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0131.csv
new file mode 100644
index 0000000000000000000000000000000000000000..61b5169f266394573537494c36c4babf12d4ade7
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0131.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+knife,0.976854,143,353,40,80
+bottle,0.961518,204,27,60,138
+cup,0.931166,208,247,50,62
+cup,0.862812,104,278,46,44
+bottle,0.780370,0,175,50,91
+cup,0.696548,52,189,51,51
+spoon,0.513593,276,230,66,22
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0132.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0132.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a0ebd5a1955e6128da392b16f052d6ef88e39249
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0132.csv
@@ -0,0 +1,8 @@
+Class,Confidence,X,Y,Width,Height
+knife,0.984781,257,356,59,101
+cup,0.973504,335,248,56,68
+cup,0.916037,215,271,81,49
+bottle,0.889368,74,146,73,102
+bottle,0.882256,325,3,46,155
+cup,0.828649,153,170,48,55
+spoon,0.599262,406,235,73,15
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0133.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0133.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7330379d1cc1698aaaa832c0bbe9d993635cbec7
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0133.csv
@@ -0,0 +1,11 @@
+Class,Confidence,X,Y,Width,Height
+knife,0.989795,374,314,72,99
+cup,0.892251,264,131,43,54
+cup,0.883950,464,213,59,75
+cup,0.863724,335,231,83,47
+bottle,0.858639,97,136,61,94
+scissors,0.789477,10,283,209,197
+bottle,0.703620,448,-1,39,132
+scissors,0.661726,0,344,38,136
+bottle,0.553078,0,156,26,128
+spoon,0.509513,524,214,88,17
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0134.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0134.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5b3a5d6f3634306a1858a2c83d37153718b11a67
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0134.csv
@@ -0,0 +1,11 @@
+Class,Confidence,X,Y,Width,Height
+scissors,0.993499,26,285,106,93
+cup,0.977328,529,172,61,68
+knife,0.962128,445,263,76,85
+bottle,0.916255,184,99,41,91
+cup,0.827923,405,188,73,45
+cup,0.795283,329,100,40,51
+bottle,0.777982,9,78,103,160
+bottle,0.762441,103,102,68,124
+scissors,0.690112,143,227,166,122
+bowl,0.527379,582,170,58,31
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0135.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0135.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a2cd19f8394976ffe1ba0117a7210eaecd7121bd
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0135.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+scissors,0.993365,169,262,84,75
+book,0.933422,0,319,127,159
+bottle,0.918718,154,63,73,162
+bottle,0.907029,231,80,51,132
+cup,0.897216,510,182,55,41
+bottle,0.834854,293,92,32,87
+cup,0.697444,425,98,37,49
+scissors,0.638979,278,212,146,108
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0136.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0136.csv
new file mode 100644
index 0000000000000000000000000000000000000000..821ad774f86b5e8b5f274c9c7c338e9221831599
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0136.csv
@@ -0,0 +1,9 @@
+Class,Confidence,X,Y,Width,Height
+scissors,0.993703,234,287,75,73
+bottle,0.987953,215,100,57,150
+bottle,0.977538,285,123,41,113
+cup,0.947123,547,206,49,38
+bottle,0.935421,331,126,30,80
+bottle,0.901309,47,-1,84,98
+cup,0.819891,454,132,33,45
+book,0.793753,1,348,192,130
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0137.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0137.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bee0023bb41805208550d9c1673428397f6c9765
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0137.csv
@@ -0,0 +1,10 @@
+Class,Confidence,X,Y,Width,Height
+scissors,0.991875,316,325,65,66
+bottle,0.932568,393,179,27,74
+bottle,0.925020,154,2,75,141
+bottle,0.741503,358,180,35,100
+cup,0.679018,505,186,32,43
+book,0.631016,116,376,164,105
+bottle,0.618654,345,176,21,81
+bottle,0.617655,295,149,44,127
+cup,0.567961,602,259,36,35
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0138.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0138.csv
new file mode 100644
index 0000000000000000000000000000000000000000..50e0abcf7016afeb01b25e6f3c372ec06f09929c
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0138.csv
@@ -0,0 +1,10 @@
+Class,Confidence,X,Y,Width,Height
+scissors,0.954241,399,294,55,54
+bottle,0.875598,9,-1,98,168
+bottle,0.872747,425,157,34,95
+bottle,0.816133,239,0,34,118
+bottle,0.725227,258,1,65,120
+book,0.705993,234,340,131,108
+bottle,0.673849,374,138,36,135
+bottle,0.658476,360,153,24,88
+bottle,0.530977,411,159,22,74
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0139.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0139.csv
new file mode 100644
index 0000000000000000000000000000000000000000..98816e65f84586a5f735073cb3b2008134421f0a
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0139.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+scissors,0.918763,422,289,57,55
+book,0.846506,264,329,124,113
+bottle,0.803975,381,150,27,87
+bottle,0.563004,430,155,27,76
+book,0.555847,59,216,163,165
+cup,0.510297,581,166,34,42
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0140.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0140.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e45313ccd1c205929e8b1cd249b3c3b76a59565f
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0140.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+scissors,0.967444,439,287,54,52
+book,0.812808,282,322,123,110
+book,0.669970,85,203,151,166
+bottle,0.656755,396,145,29,90
+cup,0.591553,598,168,35,41
+bottle,0.541549,495,156,24,72
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0141.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0141.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0b13d87db4e4213a603063e2ed2f92a6c514160e
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0141.csv
@@ -0,0 +1,11 @@
+Class,Confidence,X,Y,Width,Height
+book,0.879281,358,311,119,116
+bottle,0.798459,403,0,50,109
+book,0.763706,188,193,119,148
+scissors,0.760124,514,290,55,48
+bottle,0.667816,523,156,26,75
+bottle,0.656672,182,1,70,127
+bottle,0.646596,497,122,34,75
+bottle,0.615565,381,-1,33,100
+bottle,0.611417,476,144,26,89
+bottle,0.532552,544,150,36,92
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0142.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0142.csv
new file mode 100644
index 0000000000000000000000000000000000000000..46f6f0257626d45cbbb9f00cbe9dc846fdc8d675
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0142.csv
@@ -0,0 +1,6 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.969691,347,-3,50,148
+bottle,0.968720,300,-1,44,138
+bottle,0.806624,526,-1,46,132
+book,0.580290,327,211,113,154
+book,0.509786,500,344,138,135
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0143.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0143.csv
new file mode 100644
index 0000000000000000000000000000000000000000..858bd2b021568c70770f3eec66df752ab2400349
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0143.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.947318,338,17,43,135
+bottle,0.941929,382,16,54,144
+bottle,0.871363,563,2,58,151
+bottle,0.722885,592,2,48,156
+sports ball,0.666290,156,1,193,158
+book,0.561201,528,365,112,115
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0144.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0144.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5eb713d03af2a0e9a5cf2ef0724a5ce1849bb8ba
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0144.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.946772,400,27,50,141
+bottle,0.906269,356,25,40,127
+bottle,0.669507,609,15,31,158
+bottle,0.649078,576,6,57,160
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0145.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0145.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a4b45ef9ad914cdad5720b4934922684ea29f656
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0145.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+sports ball,0.874030,185,2,190,165
+bottle,0.856616,590,12,51,167
+bottle,0.742552,365,23,42,138
+bottle,0.723210,406,28,58,141
+book,0.570041,545,387,95,93
+book,0.504106,373,240,123,149
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0146.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0146.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7547eb929bd09f56d30564d0085d4514ca70b25e
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0146.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.917078,417,37,54,142
+bottle,0.876055,599,17,41,161
+bottle,0.797019,371,37,44,134
+book,0.755267,550,392,91,88
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0147.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0147.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c09ba0590b437f266e865f7a5910b697d6481810
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0147.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.812827,428,37,52,138
+book,0.708550,558,392,83,88
+bottle,0.657987,383,32,40,130
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0148.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0148.csv
new file mode 100644
index 0000000000000000000000000000000000000000..213f7b1addbcb0229089300a41c78a446f6bd183
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0148.csv
@@ -0,0 +1,7 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.901680,391,35,43,122
+bottle,0.868428,434,41,59,133
+book,0.650006,564,397,77,83
+bottle,0.624850,617,34,23,148
+sports ball,0.585831,212,-1,191,175
+book,0.526532,397,245,114,154
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0149.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0149.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c0ef8c80a35de5faaaa02d5ba984c44809514f1f
--- /dev/null
+++ b/target/classes/vslam/BoundedInfo/KeyFrame_0149.csv
@@ -0,0 +1,5 @@
+Class,Confidence,X,Y,Width,Height
+bottle,0.874706,442,42,56,141
+bottle,0.852566,399,40,42,128
+book,0.795620,401,244,123,163
+book,0.583777,568,401,73,79
diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0150.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0150.csv
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diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0151.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0151.csv
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diff --git a/target/classes/vslam/BoundedInfo/KeyFrame_0152.csv b/target/classes/vslam/BoundedInfo/KeyFrame_0152.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0003.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0003.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9f693933ec39285d4fa14905861174f1578e561d
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0003.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0004.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0004.csv
new file mode 100644
index 0000000000000000000000000000000000000000..538656f53a9eca7f17d6080d8dd306c239b79e8e
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0005.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0005.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4fe164870ce6b2938a96454ecc245967d7b247c3
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0006.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0006.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9047154b7ad7ab8e2ecd4ba388550266f0215c06
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0006.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0007.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0007.csv
new file mode 100644
index 0000000000000000000000000000000000000000..78cb270e2ba78fe3b86fa8611b52943f74644771
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0007.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0008.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0008.csv
new file mode 100644
index 0000000000000000000000000000000000000000..eab96394c4e7bc7836ec7a82e263dd4b68f14b62
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0008.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0009.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0009.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5e3c67fb46e54c099a932be45d7ca7445967f45a
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0009.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0010.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0010.csv
new file mode 100644
index 0000000000000000000000000000000000000000..aa4c152e3bebda655e536cfe9a7c0d6eb576d3a8
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0010.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0011.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0011.csv
new file mode 100644
index 0000000000000000000000000000000000000000..44c227519ff4c9cb642233cac73efec80ae81df2
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0011.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0012.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0012.csv
new file mode 100644
index 0000000000000000000000000000000000000000..821c019be09501bcf4d843632f1101049865039b
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0012.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0013.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0013.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e1a8f1c1bdff9a9b2903cccfc2e2a3363ebab79d
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0013.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0014.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0014.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b05ba6a3e8900363921ede25c2be0c76bb87a251
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0014.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0015.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0015.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e800c12cb1cf7f640ca5b1588799bd8ce5a6f7b4
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0015.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0016.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0016.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e8a627e03969a501d8bafaf71eb5b996159deba0
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0017.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0017.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3d0a7f761d8bce6335c3a800b08d2b9a36de8b3a
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0018.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0018.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9bf44c6d9b20eebf7c33150e3dfb78b206afb846
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0019.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0019.csv
new file mode 100644
index 0000000000000000000000000000000000000000..38e591ddeeabe9842154bda5bc4b5e2b5b112d1a
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0020.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0020.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c68f187131469ca16ce04418ad537379cdbc6bb4
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0020.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0021.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0021.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0312843d2c6c0ebdace49f7e41448f5991351b6a
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0021.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0022.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0022.csv
new file mode 100644
index 0000000000000000000000000000000000000000..70a2b735964f505fba513326e2a9f9d14c170e96
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0022.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0023.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0023.csv
new file mode 100644
index 0000000000000000000000000000000000000000..85d3faaa08994ecd5c34bad682646cf95c946d6a
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0023.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0024.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0024.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ebd9a4cd8c51fe6d5e510b3429c24daa82fe2d6a
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0024.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0025.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0025.csv
new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0026.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0026.csv
new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0027.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0027.csv
new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0028.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0028.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0683ec528b216b38ae0a50941a4e8456b2512faa
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0029.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0029.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0030.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0030.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0031.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0031.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0032.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0032.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fa51d7e72b2bf9fccb295b530cfca1a581b4313c
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0033.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0033.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0034.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0034.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c76bc576bc3c202ec931b006a46b7eadae18ad99
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0034.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0035.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0035.csv
new file mode 100644
index 0000000000000000000000000000000000000000..83d840e0f7d30dfb55ed2860f92497f90d73cc4f
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0036.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0036.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8078f6e4126e0110aa9a01888832a0e852508267
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0037.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0037.csv
new file mode 100644
index 0000000000000000000000000000000000000000..25458359113732413aa3fe420e1e1b025a613a7a
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0037.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0038.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0038.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3875596b5943c010b6fbc2073308a7ab5a4df192
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0039.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0039.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c6045a570a1b54ebe83e4ee797669663447f4e55
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0040.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0040.csv
new file mode 100644
index 0000000000000000000000000000000000000000..047dd671ef917af2040f11c252b7adb0cc45aaf5
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0040.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0041.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0041.csv
new file mode 100644
index 0000000000000000000000000000000000000000..870ea00cf6bfeda2683ffa4ce2f432a42a28e289
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0042.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0042.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3db99198e153d9c695f98bb3d28553e22935769c
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0042.csv
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new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0044.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0044.csv
new file mode 100644
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new file mode 100644
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new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0047.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0047.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0048.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0048.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1ab4888b769cc4c0d00d3e5bd46d390ea29f3e48
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0049.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0049.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9b81cbe43bb352fd77b85c1e2ef82de1eb9f23ca
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0050.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0050.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e7f0067ec984784c3e762fa521b110f153c13823
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0050.csv
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new file mode 100644
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new file mode 100644
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new file mode 100644
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new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0056.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0056.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0057.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0057.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fe9b32fc24a5e83fa9a614e34bf6d52d3d5e1576
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0058.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0058.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4f30095e5e823d04af810f93a540cb93cf8944a7
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0059.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0059.csv
new file mode 100644
index 0000000000000000000000000000000000000000..22ac231b999c1a006a27484f39137a3895b6515e
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0060.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0060.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0061.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0061.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0062.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0062.csv
new file mode 100644
index 0000000000000000000000000000000000000000..52178b08f5d7151db980205616191ed4f9131f6e
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0063.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0063.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e4331b3bf2825e79bc442b0b55ffa20d405f9fe6
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0064.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0064.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b92d656a68747405eeb9c5560a29fe1be38bb4e5
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0065.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0065.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0e1586b2024e2b29f45c300a5d723fced8f81e7f
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0066.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0066.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c0fb0ef4ef32010ada2adf073e2adcc3be0ed9ec
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0067.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0067.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cff9e5fa1e8678a04fce7897354abeeed9b924f2
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0068.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0068.csv
new file mode 100644
index 0000000000000000000000000000000000000000..48a15cb8aaa5217b384544fcaa41911194cdf3ae
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0068.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0069.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0069.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f9548a2c154dfaab5f4e4535deadac3a39526f3a
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0069.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0070.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0070.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d3fd4fe123e5ff0d196bc7f17e0bca211d9d1104
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0070.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0071.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0071.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f2d4bc8154ffb0c9cec6c70d0d56c0611ba0d11a
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0071.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0072.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0072.csv
new file mode 100644
index 0000000000000000000000000000000000000000..61a6fc1478d5f8f4ab04192a5a48303bdba6becc
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0073.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0073.csv
new file mode 100644
index 0000000000000000000000000000000000000000..005cebcf8d66f5ff226d78470b4b911fc6147c4d
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0073.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0074.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0074.csv
new file mode 100644
index 0000000000000000000000000000000000000000..739e125dc709bbfca9366cb20b039aa599c10f9b
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0075.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0075.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6756bc7bc8d28f771545d5b3548778a55fde3b16
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0075.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0076.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0076.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2199d66e64258614f39f01d14fcb11699eb0e691
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0076.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0077.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0077.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3f27b52d8b683fff92f0b0eb3d1abc86703d78b9
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0077.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0078.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0078.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c6486371e8869d22f5c3c22218dce1aee2d34962
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0078.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0079.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0079.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4cef320261818f97995567f9f90739f001777be4
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0079.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0080.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0080.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5d9d8436c9c7584232a7610e74e018049af70900
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0080.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0081.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0081.csv
new file mode 100644
index 0000000000000000000000000000000000000000..83127af673f63567c386ec3fc8064482d22a0c74
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0081.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0082.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0082.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5f8fec5e997ebaf2ce1294b779fa8d2794c15b9c
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0082.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0083.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0083.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cccb292f5e54fad2bb74e3f8237f789cae9d8498
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0083.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0084.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0084.csv
new file mode 100644
index 0000000000000000000000000000000000000000..de82eace6ba63200135215ebcf89564d720eec91
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0084.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0085.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0085.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0ab985cf523cfb05e3b7710cfbb025bfc7ad329b
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0085.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0086.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0086.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b6882ecdc6309349f9ca4653402451272f9f636c
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0086.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0087.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0087.csv
new file mode 100644
index 0000000000000000000000000000000000000000..562799c0c439293451957b6294991fbd98310d2b
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0087.csv
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diff --git a/target/classes/vslam/KeyFramePoints/KeyFramePoints_0088.csv b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0088.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2eb93edb526f1a12e51184d964ebb34e960ac16b
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints/KeyFramePoints_0088.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0003.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0003.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7e78a2761a851fa9d51ae6237da8752f10406bc7
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0003.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0004.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0004.csv
new file mode 100644
index 0000000000000000000000000000000000000000..aa05c776c6359c71e8e466686635e6606bb192bd
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0004.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0005.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0005.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0dfd8d314715476f5ced7aa2762ada1553c17786
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0007.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0007.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0008.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0008.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4f5c2649312fc739233f0d51ddb38980a3bf82d4
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0009.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0009.csv
new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0010.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0010.csv
new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0011.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0011.csv
new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0012.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0012.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0c7b8b191dbadf2cae77d0355d79236e45ae3b4b
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0013.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0013.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0bce2f31a6db3dba3f1cc6a423b120938fc3d17e
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0014.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0014.csv
new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0015.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0015.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0016.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0016.csv
new file mode 100644
index 0000000000000000000000000000000000000000..619e5570c1698c6bac2f12f814012b7694e65a0c
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0016.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0017.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0017.csv
new file mode 100644
index 0000000000000000000000000000000000000000..11d4074cf7cbd5094c16909754e5af295c6970be
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0017.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0018.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0018.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0019.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0019.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7e0d16d9c885003d78c94d1f529ea8c0c88d50b5
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0020.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0020.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7319bed1d6e06a3721deaf63322e3841ec313911
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0020.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0021.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0021.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0022.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0022.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0023.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0023.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0024.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0024.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0025.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0025.csv
new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0026.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0026.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d96fea3c234bbcd25b65dc6548bc84e38bbf7690
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0026.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0027.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0027.csv
new file mode 100644
index 0000000000000000000000000000000000000000..439162836101aac386471853f2731585b7a77ce5
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0027.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0028.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0028.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0029.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0029.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e49d565315fae5d4d020eaeccfc421650573ad05
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0030.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0030.csv
new file mode 100644
index 0000000000000000000000000000000000000000..551d6bdb8b0ec2e9513de9d9b0436dd39a149773
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0031.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0031.csv
new file mode 100644
index 0000000000000000000000000000000000000000..98b1e6e06856023f54025f32300a823abeb218e9
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0031.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0032.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0032.csv
new file mode 100644
index 0000000000000000000000000000000000000000..245f4932942dbfbc2135be5fe3e08b594a7fb413
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0032.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0033.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0033.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3b11db1fd7ddd16ed024bfbf22d70b1fd3b28a8b
--- /dev/null
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new file mode 100644
index 0000000000000000000000000000000000000000..3c6e5098c6434d6c774d4f57da9dea1399b20d15
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0035.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0035.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0036.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0036.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e6edcfcefa99e40a279a25266375e43c7deff0cf
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0037.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0037.csv
new file mode 100644
index 0000000000000000000000000000000000000000..11f4de7dc3c9d66ca4f555b65767ddbb50bb3654
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0037.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0038.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0038.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f98c70e0700b580012ef45d211cde4b4cfa19a3f
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0038.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0039.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0039.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1af747ec93e4244d8ee80fcca404e2e549ddc6a5
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0039.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0040.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0040.csv
new file mode 100644
index 0000000000000000000000000000000000000000..aebead2e6b44533bb5e1b0e51bb9784886162c14
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0040.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0041.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0041.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c297e1e8c6966eafe4a65554c73eca9427937f16
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0042.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0042.csv
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index 0000000000000000000000000000000000000000..0b2b52059f019d8d09bd2f40742f86cab3b7523b
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0043.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0043.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0044.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0044.csv
new file mode 100644
index 0000000000000000000000000000000000000000..440f9a8689d267cef635da7149a061fc9b8d8063
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0044.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0045.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0045.csv
new file mode 100644
index 0000000000000000000000000000000000000000..71d25e72c77138eb51240687c162e789745de926
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0046.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0046.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0047.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0047.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bb6572ed5a4a100ee68fa9e8b80fa1e6b2df96cb
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0047.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0048.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0048.csv
new file mode 100644
index 0000000000000000000000000000000000000000..594e01b5db10cf0afb2b73b6ab865ca944653760
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0048.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0049.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0049.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c5ddfec95f7c4cbf1aac4b76bc0d16903dd0b56d
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0049.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0050.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0050.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d3958ed0888b1feace153e45b057c976e986c882
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0050.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0051.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0051.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8611058fadcb38857b177e66f7e1897cb5b913af
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0051.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0052.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0052.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8023646a44a8a5eb67ced2a1fd533834f6463f25
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0052.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0053.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0053.csv
new file mode 100644
index 0000000000000000000000000000000000000000..28ed751e1ada926abb268a0c721b2f96c6624e88
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0054.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0054.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0055.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0055.csv
new file mode 100644
index 0000000000000000000000000000000000000000..747a5eaf8c9b080e064ccbe479369dfc74244e7b
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0056.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0056.csv
new file mode 100644
index 0000000000000000000000000000000000000000..20d39667af6b2dc2631daa4fcb1c9f9ab1e20f6b
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0056.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0057.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0057.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0058.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0058.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6383f4cb0c5f95334e7fc747cfa3730f2be819a4
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0059.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0059.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3319b5e646e818b027157a19edddcdbb23f608cf
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0060.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0060.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0061.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0061.csv
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index 0000000000000000000000000000000000000000..df982b02fa8763e227bae1f9d32e193d6d55f61e
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0062.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0062.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0063.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0063.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0064.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0064.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0065.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0065.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7c434f24eae5fae3946170241917b437634ba676
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0066.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0066.csv
new file mode 100644
index 0000000000000000000000000000000000000000..adf105a555edd5796b18585da33bc556a905f522
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0067.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0067.csv
new file mode 100644
index 0000000000000000000000000000000000000000..13cc3f5b051ba1c93bfb7e6bbf8e6831a2ecbb56
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0068.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0068.csv
new file mode 100644
index 0000000000000000000000000000000000000000..33dae7982c6077ca12fbd995cfdc453e7f47bc95
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0068.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0069.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0069.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4edd4333fb33c0fbed80cd7fd49133c954d272db
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0070.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0070.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7d7816a2d600fc13c3f974451bc6a34fd74838dc
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0070.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0071.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0071.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ef7bb27122b279f4eb52924520e3eaed5efc76da
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0071.csv
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new file mode 100644
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new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0074.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0074.csv
new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0075.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0075.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0f628ceb9e4b478610d8096d5db43fbb9c920240
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0076.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0076.csv
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index 0000000000000000000000000000000000000000..5044ea47c96a3c906f85d6678a9ca400b4f8f430
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0077.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0077.csv
new file mode 100644
index 0000000000000000000000000000000000000000..eb8e11c2455e89531bf9ae7c133f0258cb2b7755
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0078.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0078.csv
new file mode 100644
index 0000000000000000000000000000000000000000..68092080c83f28306bfc927118db32c15212d4e9
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0079.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0079.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2844546c38323735ec7601ac63efaf3ccbb0579f
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0080.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0080.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0081.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0081.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9fc8a51c05f38db005ae7e57516b38fe37c57a7e
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0082.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0082.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9fac3bdb773830dcdb6cebbdea5f7b0529f0fcf5
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0083.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0083.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0084.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0084.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b88d8c3b3339dd4740fdfb1cc641a661e0889b2f
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0085.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0085.csv
new file mode 100644
index 0000000000000000000000000000000000000000..574b95d6ac9a1ada238f5cf840b55f7e4bb688c1
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0085.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0086.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0086.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d3fc287861385572ce5ee8795605b493d81272c1
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0087.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0087.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0088.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0088.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0089.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0089.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5507921fd9e6fe9ba221e2e9fd80cba1937ab7c4
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0090.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0090.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0091.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0091.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3b839f526140db5e4b7cc42843c9c9e7e0274307
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0092.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0092.csv
new file mode 100644
index 0000000000000000000000000000000000000000..184c4a7b0c39b41bd4d29a74d61292252d380071
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0093.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0093.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cd8e08784e98d94cfdd6aaf4b54a8b1485056597
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0093.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0094.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0094.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a233f36d7d9bad09da37f06a968d03e4074405e4
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0095.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0095.csv
new file mode 100644
index 0000000000000000000000000000000000000000..47376610d5ee562b5c92733019f5b910fcbfe997
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0096.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0096.csv
new file mode 100644
index 0000000000000000000000000000000000000000..198ba2723cfa8d6e3b337ced66178e36cf783ae9
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0097.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0097.csv
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index 0000000000000000000000000000000000000000..a535873b8d8a405960ac7f41cc79914b2ddce9b0
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0098.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0098.csv
new file mode 100644
index 0000000000000000000000000000000000000000..07a6c19557e31ccc6dac42a0f07f616420efab6d
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0099.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0099.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6ad4dcd901b219d08709f87d1f88768fa3d47a25
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0100.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0100.csv
new file mode 100644
index 0000000000000000000000000000000000000000..74f5df7270486ee1c56505f0b11ad6fe77bfdc6d
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0100.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0101.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0101.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b3d1acfc52ca4f7e774accf0fed94fcbfe1ef991
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0102.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0102.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1708a1425f0bf670db2466b530257fdcdfa64d80
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0103.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0103.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c0ce8c6a259186a887f82600eb102ac28fe7778c
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0104.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0104.csv
new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0105.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0105.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f43bf7c27fc0260a35a5d4b22481d3d6b5618ef2
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0106.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0106.csv
new file mode 100644
index 0000000000000000000000000000000000000000..449341e2722c8835e947ec7a7b23e82d2435ce9a
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0107.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0107.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a22ce2dade422579ec229d01a88500d0ade05a23
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0107.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0108.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0108.csv
new file mode 100644
index 0000000000000000000000000000000000000000..25f82f717195aab90a5014d10cd8c0535fee832f
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0109.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0109.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3b59b4ca533e316fbbabd1737394b2eac60a13b7
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0110.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0110.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1092c689d9152bffa72ca10724dcb7c6880e1e4d
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0111.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0111.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6831f16b71a1a13cac578b31cd14e1b957a47a78
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0112.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0112.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a3a9a9d8396f328af6408a8f99468e742a75a809
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0113.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0113.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bc5ce67b6455e0c7c47c39e09c29d1ce17fbb6f5
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0114.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0114.csv
new file mode 100644
index 0000000000000000000000000000000000000000..70e00abe843e32071f6533179cd472a9a44ea166
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0114.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0115.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0115.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fe9e67d2a9ce9ac3ec0b245212985c8d6d91fb71
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0115.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0116.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0116.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f2d1cdbfb58a583e433abe233954273d16d22dc1
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0117.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0117.csv
new file mode 100644
index 0000000000000000000000000000000000000000..27d0fd6f44e7ee53382ddf779a728ecde2adb6e8
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new file mode 100644
index 0000000000000000000000000000000000000000..4c61aba0678251f5d913de2033ea7d00fc195618
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0119.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0119.csv
new file mode 100644
index 0000000000000000000000000000000000000000..89951bb1d90cb02b6279cf45bc6a16772e9faff0
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0119.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0120.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0120.csv
new file mode 100644
index 0000000000000000000000000000000000000000..47f285ff28bce808f2d010c2d2c2be6ca36c4e62
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0121.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0121.csv
new file mode 100644
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new file mode 100644
index 0000000000000000000000000000000000000000..7f36d9a89fde12b2210cf590d94d95527e4339f1
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0123.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0123.csv
new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0124.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0124.csv
new file mode 100644
index 0000000000000000000000000000000000000000..79fcca7adc4a0f2bbcb619947f5b72e6fc18817f
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0125.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0125.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0e2aba3323e9768ad4b3cc1adbe627bf5c6fb72f
--- /dev/null
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new file mode 100644
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0127.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0127.csv
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0128.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0128.csv
new file mode 100644
index 0000000000000000000000000000000000000000..35c7f7b7ef93a13efcc1538568caa5b6e0e669da
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0129.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0129.csv
new file mode 100644
index 0000000000000000000000000000000000000000..42c305aebab94022edb99f1d7169f59f16830083
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0129.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0130.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0130.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0131.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0131.csv
new file mode 100644
index 0000000000000000000000000000000000000000..98bbc5b4424ae922bea6df547c56f2694c626481
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0133.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0133.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a4a2ab59331a331bb10c5fceaf0f0eb5daefdb5b
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0133.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0134.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0134.csv
new file mode 100644
index 0000000000000000000000000000000000000000..20c985d2a3c3f77393235f60ad91abbaba332a37
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0135.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0135.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0c63c1bbf892512d6f1c005898205094564d1a69
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0136.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0136.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d0035f3dc40ffb53c2b80cabbfddea2ce9a37b75
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0136.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0137.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0137.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6df85647f1940f7acb146e6905d52bfacb2abe18
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0137.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0138.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0138.csv
new file mode 100644
index 0000000000000000000000000000000000000000..eebc670f2a9fa15cd1fb4db246c3f920c22d1039
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0138.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0139.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0139.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4c3fbdf4f3fbc19ba5a68f6e00f8e68454372f46
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0140.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0140.csv
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index 0000000000000000000000000000000000000000..52a7d648533b15ae7460ceeaa03e9b7596165bac
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0141.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0141.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f5188885604dab8710eae274fcdc84c284da1b15
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0142.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0142.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b370bb9869305d7998dd4de81c26b94bcf70d686
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0142.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0143.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0143.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e14dd6ff6facc62cd1f096ba8b86cc560aef4b88
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0144.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0144.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e6487284e759c3bc53fd97b29c684c0db677b94b
--- /dev/null
+++ b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0144.csv
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index 0000000000000000000000000000000000000000..1b933d75dbae7fe72ac4f38d3ad9179b2ac3de94
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0146.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0146.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0147.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0147.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0149.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0149.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f54837fa05ae84f6ffdb39fdd1f6334f46ba6f9f
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0150.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0150.csv
new file mode 100644
index 0000000000000000000000000000000000000000..71d8cda0d6f60e9e30cbcf1ba5094bfa31cac603
--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0151.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0151.csv
new file mode 100644
index 0000000000000000000000000000000000000000..04c63f04231cc2d6b781cce3757e789e1ccab705
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0153.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0153.csv
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new file mode 100644
index 0000000000000000000000000000000000000000..1d61e5bb45a7182614c36d98cad24d95e1325f48
--- /dev/null
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new file mode 100644
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new file mode 100644
index 0000000000000000000000000000000000000000..adfa38baa213619154c2f0ae803432e5f0813764
--- /dev/null
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new file mode 100644
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--- /dev/null
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0158.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0158.csv
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diff --git a/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0159.csv b/target/classes/vslam/KeyFramePoints_Mono/KeyFramePoints_0159.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c3bb7b9ff3157d7c5a524b5656757671be652f1d
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diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/MonocularVisualSimultaneousLocalizationAndMappingExample.mlx b/target/classes/vslam/Mathworks_VSLAM_Example/MonocularVisualSimultaneousLocalizationAndMappingExample.mlx
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diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/bagOfFeaturesDataSLAM.mat b/target/classes/vslam/Mathworks_VSLAM_Example/bagOfFeaturesDataSLAM.mat
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diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperAddLoopConnections.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperAddLoopConnections.m
new file mode 100644
index 0000000000000000000000000000000000000000..8c4ece7be009a3705b802813b4ad6fb04a36e0d1
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperAddLoopConnections.m
@@ -0,0 +1,94 @@
+function [isLoopClosed, mapPoints, vSetKeyFrames] = helperAddLoopConnections(...
+    mapPoints, vSetKeyFrames, loopCandidates, currKeyFrameId, currFeatures, ...
+    loopEdgeNumMatches)
+%helperAddLoopConnections add connections between the current key frame and
+%   the valid loop candidate key frames. A loop candidate is valid if it has
+%   enough covisible map points with the current key frame.
+
+%   This is an example helper function that is subject to change or removal
+%   in future releases.
+
+%   Copyright 2019-2023 The MathWorks, Inc.
+%#codegen
+
+loopClosureEdge = zeros(0, 2, 'uint32');
+
+numCandidates   = size(loopCandidates,1);
+if isSimMode
+    [index3d1, index2d1] = findWorldPointsInView(mapPoints, currKeyFrameId);
+else
+    [index3d1Cg, index2d1Cg] = findWorldPointsInView(mapPoints, currKeyFrameId);
+    index2d1 = index2d1Cg{1};
+    index3d1 = index3d1Cg{1};
+end
+
+validFeatures1  = currFeatures.Features(index2d1, :);
+
+for k = 1 : numCandidates
+    if isSimMode()
+        [index3d2, index2d2] = findWorldPointsInView(mapPoints, loopCandidates(k));
+    else
+        [index3d2Cg, index2d2Cg] = findWorldPointsInView(mapPoints, loopCandidates(k));
+        index2d2 = index2d2Cg{1};
+        index3d2 = index3d2Cg{1};
+    end
+    allFeatures2   = vSetKeyFrames.Views.Features{loopCandidates(k)};
+
+    validFeatures2 = allFeatures2(index2d2, :);
+
+    indexPairs = matchFeatures(binaryFeatures(validFeatures1), binaryFeatures(validFeatures2), ...
+        'Unique', true, 'MaxRatio', 0.9, 'MatchThreshold', 40);
+
+    % Check if all the candidate key frames have strong connection with the
+    % current keyframe
+    if size(indexPairs, 1) < loopEdgeNumMatches
+        continue
+    end
+
+    % Estimate the relative pose of the current key frame with respect to the
+    % loop candidate keyframe with the highest similarity score
+    worldPoints1 = mapPoints.WorldPoints(index3d1(indexPairs(:, 1)), :);
+    worldPoints2 = mapPoints.WorldPoints(index3d2(indexPairs(:, 2)), :);
+
+    tform1 = pose2extr(vSetKeyFrames.Views.AbsolutePose(end));
+    tform2 = pose2extr(vSetKeyFrames.Views.AbsolutePose(loopCandidates(k)));
+
+    worldPoints1InCamera1 = transformPointsForward(tform1, worldPoints1) ;
+    worldPoints2InCamera2 = transformPointsForward(tform2, worldPoints2) ;
+
+    w = warning('off','all');
+    if isSimMode()
+        [tform, inlierIndex] = estgeotform3d(...
+            worldPoints1InCamera1, worldPoints2InCamera2, 'similarity', 'MaxDistance', 0.1);
+    else
+        [tform, inlierIndex] = estgeotform3d(...
+            worldPoints1InCamera1, worldPoints2InCamera2, 'rigid', 'MaxDistance', 0.1);
+    end
+    warning(w);
+
+    % Add connection between the current key frame and the loop key frame
+    inlierIndexVals = inlierIndex(:);
+    indexPairs1 = indexPairs(inlierIndexVals, 1);
+    indexPairs2 = indexPairs(inlierIndexVals, 2);
+    index2dPairs = index2d2(indexPairs2);
+    index2d1Pairs = index2d1(indexPairs1);
+    matches = uint32([index2dPairs, index2d1Pairs]);
+    vSetKeyFrames = addConnection(vSetKeyFrames, loopCandidates(k), currKeyFrameId, tform, 'Matches', matches);
+    if isSimMode()
+        disp(['Loop edge added between keyframe: ', num2str(loopCandidates(k)), ' and ', num2str(currKeyFrameId)]);
+    end
+
+    % Fuse co-visible map points
+    matchedIndex3d1 = index3d1(indexPairs1);
+    matchedIndex3d2 = index3d2(indexPairs2);
+
+    mapPoints = updateWorldPoints(mapPoints, matchedIndex3d1, mapPoints.WorldPoints(matchedIndex3d2, :));
+
+    loopClosureEdge = [loopClosureEdge; loopCandidates(k), currKeyFrameId];
+end
+isLoopClosed = ~isempty(loopClosureEdge);
+end
+
+function tf = isSimMode()
+tf = isempty(coder.target);
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperAddNewKeyFrame.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperAddNewKeyFrame.m
new file mode 100644
index 0000000000000000000000000000000000000000..8171da4598e2f5e654d532de5f2eafe794b88a54
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperAddNewKeyFrame.m
@@ -0,0 +1,54 @@
+function [mapPoints, vSetKeyFrames] = helperAddNewKeyFrame(mapPoints, vSetKeyFrames,...
+    cameraPose, currFeatures, currPoints, mapPointsIndices, featureIndices, keyFramesIndices)
+%helperAddNewKeyFrame add key frames to the key frame set
+%
+%   This is an example helper function that is subject to change or removal
+%   in future releases.
+
+%   Copyright 2019-2023 The MathWorks, Inc.
+%#codegen
+
+viewId = vSetKeyFrames.Views.ViewId(end)+1;
+
+vSetKeyFrames = addView(vSetKeyFrames, viewId, cameraPose,...
+    'Features', currFeatures.Features, ...
+    'Points', currPoints);
+
+viewsAbsPoses = vSetKeyFrames.Views.AbsolutePose;
+
+for i = 1:numel(keyFramesIndices)
+    localKeyFrameId = keyFramesIndices(i);
+    if isSimMode()
+        [index3d, index2d] = findWorldPointsInView(mapPoints, localKeyFrameId);
+    else
+        [index3dCg, index2dCg] = findWorldPointsInView(mapPoints, localKeyFrameId);
+        index3d = index3dCg{1};
+        index2d = index2dCg{1};
+    end
+    [~, ia, ib] = intersect(index3d, mapPointsIndices, 'stable');
+
+    prePose   = viewsAbsPoses(localKeyFrameId);
+    relPose = rigidtform3d(prePose.R' * cameraPose.R, ...
+        (cameraPose.Translation-prePose.Translation)*prePose.R);
+
+    if numel(ia) > 5
+        if isSimMode()
+            vSetKeyFrames = addConnection(vSetKeyFrames, localKeyFrameId, viewId, relPose, ...
+                'Matches', [index2d(ia),featureIndices(ib)]);
+        else
+            coder.varsize('matches', [inf 2], [1, 0]);
+            fIndices = featureIndices(ib(:));
+            matches = [index2d(ia), fIndices];
+            vSetKeyFrames = addConnection(vSetKeyFrames, localKeyFrameId, viewId, relPose, ...
+                'Matches', matches);
+        end
+    end
+end
+
+mapPoints = addCorrespondences(mapPoints, viewId, mapPointsIndices, ...
+    featureIndices);
+end
+
+function tf = isSimMode()
+    tf = isempty(coder.target);
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperCheckLoopClosure.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperCheckLoopClosure.m
new file mode 100644
index 0000000000000000000000000000000000000000..7cff3e85c2f308126c160e6d73176923a5b38914
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperCheckLoopClosure.m
@@ -0,0 +1,58 @@
+function [isDetected, loopKeyFrameIds] = helperCheckLoopClosure(vSetKeyFrames, ...
+    currKeyframeId, imageDatabase, currImg, loopEdgeNumMatches)
+%helperCheckLoopClosure detect loop candidates key frames by retrieving
+%   visually similar images from the feature database.
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2019-2023 The MathWorks, Inc.
+%#codegen
+
+% Retrieve all the visually similar key frames
+[candidateViewIds, similarityscores] = retrieveImages(currImg, imageDatabase);
+
+% Compute similarity between the current key frame and its strongly-connected 
+% key frames. The minimum similarity score is used as a baseline to find 
+% loop candidate key frames, which are visually similar to but not connected 
+% to the current key frame
+covisViews          = connectedViews(vSetKeyFrames, currKeyframeId);
+covisViewsIds       = covisViews.ViewId;
+strongCovisViews    = connectedViews(vSetKeyFrames, currKeyframeId, 'MinNumMatches', loopEdgeNumMatches);
+strongCovisViewIds  = strongCovisViews.ViewId;
+
+% Retrieve the top 10 similar connected key frames
+[~,~,scores] = evaluateImageRetrieval(currImg, imageDatabase, strongCovisViewIds, 'NumResults', 10);
+minScore     = min(scores);
+
+[loopKeyFrameIds,ia] = setdiff(candidateViewIds, covisViewsIds, 'stable');
+
+% Scores of non-connected key frames
+candidateScores  = similarityscores(ia); % Descending
+
+if ~isempty(ia)
+    bestScore       = candidateScores(1);
+    
+    % Score must be higher than the 75% of the best score 
+    isValid         = candidateScores > max(bestScore*0.75, minScore);
+    
+    loopKeyFrameIds = loopKeyFrameIds(isValid);
+else
+    loopKeyFrameIds = zeros(coder.ignoreConst(0), coder.ignoreConst(0), class(loopKeyFrameIds));
+end
+
+% Loop candidates need to be consecutively detected
+minNumCandidates = 3; % At least 3 candidates are found
+if size(loopKeyFrameIds,1) >= minNumCandidates
+    groups = nchoosek(loopKeyFrameIds, minNumCandidates);
+    consecutiveGroups = groups(max(groups,[],2) - min(groups,[],2) < 4, :);
+    if ~isempty(consecutiveGroups) % Consecutive candidates are found
+        loopKeyFrameIds = consecutiveGroups(1,:);
+        isDetected = true;
+    else
+        isDetected = false;
+    end
+else
+    isDetected = false;
+end
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperCreateNewMapPoints.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperCreateNewMapPoints.m
new file mode 100644
index 0000000000000000000000000000000000000000..1731749fa36785ad66beb4aa0763f71a1c072255
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperCreateNewMapPoints.m
@@ -0,0 +1,205 @@
+function [mapPoints, vSetKeyFrames, recentPointIdx] = helperCreateNewMapPoints(...
+    mapPoints, vSetKeyFrames, currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax)
+%helperCreateNewMapPoints creates new map points by triangulating matched
+%   feature points in the current key frame and the connected key frames.
+%
+%   This is an example helper function that is subject to change or removal
+%   in future releases.
+
+%   Copyright 2019-2023 The MathWorks, Inc.
+%#codegen
+
+% Get connected key frames
+KcViews  = connectedViews(vSetKeyFrames, currKeyFrameId, 'MinNumMatches', minNumMatches);
+KcIDs    = KcViews.ViewId;
+
+% Retreive data of the current key frame
+views = vSetKeyFrames.Views;
+currPose        = views.AbsolutePose(currKeyFrameId);
+currFeatures    = views.Features{currKeyFrameId};
+currPoints      = views.Points{currKeyFrameId};
+currLocations   = currPoints.Location;
+currScales      = currPoints.Scale;
+
+% Camera projection matrix
+currCamMatrix   = cameraProjection(intrinsics, pose2extr(currPose));
+
+recentPointIdx  = zeros(0, 1);
+for i = 1:numel(KcIDs)
+    kfPose      = views.AbsolutePose(KcIDs(i));
+    if isSimMode()
+        [kfIndex3d, kfIndex2d] = findWorldPointsInView(mapPoints, KcIDs(i));
+    else
+        [kfIndex3dCg, kfIndex2dCg] = findWorldPointsInView(mapPoints, KcIDs(i));
+        kfIndex3d = kfIndex3dCg{1};
+        kfIndex2d = kfIndex2dCg{1};
+    end
+    xyzPoints   = mapPoints.WorldPoints(kfIndex3d,:);
+    medianDepth = median(vecnorm(xyzPoints - kfPose.Translation, 2, 2));
+
+    % Skip the key frame is the change of view is small
+    isViewClose = norm(kfPose.Translation - currPose.Translation)/medianDepth < 0.01;
+    
+    if isViewClose
+        continue
+    end
+
+    % Retrieve data of the connected key frame
+    kfFeatures  = views.Features{KcIDs(i)};
+    kfPoints    = views.Points{KcIDs(i)};
+    kfLocations = kfPoints.Location;
+    kfScales    = kfPoints.Scale;
+
+    % currIndex2d changes in each iteration as new map points are created
+    if isSimMode()
+        [~, currIndex2d] = findWorldPointsInView(mapPoints, currKeyFrameId);
+    else
+        [~, currIndex2dCg] = findWorldPointsInView(mapPoints, currKeyFrameId);
+        currIndex2d = currIndex2dCg{1};
+    end
+    % Only use unmatched feature points
+    uIndices1   = setdiff(uint32(1:size(kfFeatures,1))',  kfIndex2d, 'stable');
+    uIndices2   = setdiff(uint32(1:size(currFeatures,1))', currIndex2d, 'stable');
+
+    uFeatures1  = kfFeatures(uIndices1, :);
+    uFeatures2  = currFeatures(uIndices2, :);
+
+    uLocations1 = kfLocations(uIndices1, :);
+    uLocations2 = currLocations(uIndices2, :);
+
+    uScales1    = kfScales(uIndices1);
+    uScales2    = currScales(uIndices2);
+
+    indexPairs  = matchFeatures(binaryFeatures(uFeatures1), binaryFeatures(uFeatures2),...
+        'Unique', true, 'MaxRatio', 0.7, 'MatchThreshold', 40);
+    
+    if isempty(indexPairs)
+        continue
+    end
+
+    matchedPoints1 = uLocations1(indexPairs(:,1), :);
+    matchedPoints2 = uLocations2(indexPairs(:,2), :);
+    
+    % Epipole in the current key frame
+    epiPole = world2img(kfPose.Translation, pose2extr(currPose), intrinsics);
+    distToEpipole = vecnorm(matchedPoints2 - epiPole, 2, 2);
+
+    % Compute fundamental matrix
+    F = computeF(intrinsics, kfPose, currPose);
+
+    % Epipolar line in the second image
+    epiLine = epipolarLine(F, matchedPoints2);
+    distToLine = abs(sum(epiLine.* [matchedPoints1, ones(size(matchedPoints1,1), 1)], 2))./...
+        sqrt(sum(epiLine(:,1:2).^2, 2));
+    isValid = distToLine < 2*uScales2(indexPairs(:,2)) & ...
+        distToEpipole > 10*uScales2(indexPairs(:,2));
+
+    indexPairs = indexPairs(isValid, :);
+    matchedPoints1 = matchedPoints1(isValid, :);
+    matchedPoints2 = matchedPoints2(isValid, :);
+    
+    % Parallax check
+    isLarge = isLargeParalalx(matchedPoints1, matchedPoints2, kfPose, ...
+        currPose, intrinsics, minParallax);
+
+    matchedPoints1  = matchedPoints1(isLarge, :);
+    matchedPoints2  = matchedPoints2(isLarge, :);
+    indexPairs      = indexPairs(isLarge, :);
+
+    kfCamMatrix = cameraProjection(intrinsics, pose2extr(kfPose));
+
+    % Triangulate two views to create new world points
+    [xyzPoints, reprojectionErrors, validIdx] = triangulate(matchedPoints1, ...
+        matchedPoints2, kfCamMatrix, currCamMatrix);
+
+    % Filtering by view direction and reprojection error
+    inlier = filterTriangulatedMapPoints(xyzPoints, kfPose, currPose, ...
+        uScales1(indexPairs(:,1)), uScales2(indexPairs(:,2)), ...
+        reprojectionErrors, scaleFactor, validIdx);
+
+    % Add new map points and update connections
+    if any(inlier)
+        xyzPoints   = xyzPoints(inlier,:);
+        indexPairs  = indexPairs(inlier, :);
+
+        mIndices1   = uIndices1(indexPairs(:, 1));
+        mIndices2   = uIndices2(indexPairs(:, 2));
+
+        [mapPoints, indices] = addWorldPoints(mapPoints, xyzPoints);
+        recentPointIdx       = [recentPointIdx; indices]; %#ok<AGROW>
+
+        % Add new observations
+        mapPoints  = addCorrespondences(mapPoints, KcIDs(i),indices, mIndices1);
+        mapPoints  = addCorrespondences(mapPoints, currKeyFrameId, indices, mIndices2);
+
+        % Update connections with new feature matches
+        if isSimMode()
+            [~,ia]     = intersect(vSetKeyFrames.Connections{:,1:2}, ...
+            [KcIDs(i), currKeyFrameId], 'row', 'stable');
+            oldMatches = vSetKeyFrames.Connections.Matches{ia};
+        else
+            connections = vSetKeyFrames.Connections;
+            [~,ia]     = intersect([connections.ViewId1, connections.ViewId2], ...
+                [KcIDs(i), currKeyFrameId], 'row', 'stable');
+            oldMatches = connections.Matches{ia};
+        end
+        newMatches = [oldMatches; mIndices1, mIndices2];
+        vSetKeyFrames  = updateConnection(vSetKeyFrames, KcIDs(i), currKeyFrameId, ...
+            'Matches', newMatches);
+    end
+end
+end
+
+function F = computeF(intrinsics, pose1, pose2)
+R1 = pose1.R;
+t1 = pose1.Translation';
+
+R2 = pose2.R;
+t2 = pose2.Translation';
+
+R12 = R1'*R2;
+t12 = R1'*(t2-t1);
+
+% Skew symmetric matrix
+t12x = [0, -t12(3), t12(2)
+    t12(3), 0, -t12(1)
+    -t12(2) t12(1), 0];
+
+F = intrinsics.K'\ t12x * R12 / intrinsics.K;
+end
+
+function inlier = filterTriangulatedMapPoints(xyzPoints, pose1, pose2, ...
+    scales1, scales2, reprojectionErrors, scaleFactor, isInFront)
+
+camToPoints1= xyzPoints - pose1.Translation;
+camToPoints2= xyzPoints - pose2.Translation;
+
+% Check scale consistency and reprojection errors
+distances1  = vecnorm(camToPoints1, 2, 2);
+distances2  = vecnorm(camToPoints2, 2, 2);
+ratioDist   = distances1./distances2;
+ratioScale  = scales2./scales1;
+
+ratioFactor = 1.5 * scaleFactor;
+
+isInScale   = (ratioDist./ratioScale < ratioFactor  |  ...
+    ratioScale./ratioDist < ratioFactor);
+
+maxError    = sqrt(6);
+isSmallError= reprojectionErrors < maxError*min(scales1, scales2);
+inlier      = isInScale & isSmallError & isInFront;
+end
+
+function isLarge = isLargeParalalx(points1, points2, pose1, pose2, intrinsics, minParallax)
+
+% Parallax check
+ray1 = [points1, ones(size(points1(:,1)))]/intrinsics.K' *pose1.R';
+ray2 = [points2, ones(size(points1(:,2)))]/intrinsics.K' *pose2.R';
+
+cosParallax = sum(ray1 .* ray2, 2) ./(vecnorm(ray1, 2, 2) .* vecnorm(ray2, 2, 2));
+isLarge     = cosParallax < cosd(minParallax) & cosParallax > 0;
+end
+
+function tf = isSimMode()
+    tf = isempty(coder.target);
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperImportGroundTruth.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperImportGroundTruth.m
new file mode 100644
index 0000000000000000000000000000000000000000..8c9488ba53b88a69711a59deed543ca532bae1e8
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperImportGroundTruth.m
@@ -0,0 +1,57 @@
+function camPoses = helperImportGroundTruth(fileName, imds)
+%helperImportGroundTruth Import ground truth camera poses from a .txt file
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+%
+%   Copyright 2023 The MathWorks Inc.
+
+% Set up the Import Options and import the data
+opts = delimitedTextImportOptions("NumVariables", 9);
+
+% Specify range and delimiter
+opts.DataLines = [4, Inf];
+opts.Delimiter = " ";
+
+% Specify column names and types
+opts.VariableNames = ["timestamp", "tx", "ty", "tz", "qx", "qy", "qz", "qw", "Var9"];
+opts.SelectedVariableNames = ["timestamp", "tx", "ty", "tz", "qx", "qy", "qz", "qw"];
+opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double", "string"];
+
+% Specify file level properties
+opts.ExtraColumnsRule = "ignore";
+opts.EmptyLineRule = "read";
+opts.ConsecutiveDelimitersRule = "join";
+opts.LeadingDelimitersRule = "ignore";
+
+% Specify variable properties
+opts = setvaropts(opts, "Var9", "WhitespaceRule", "preserve");
+opts = setvaropts(opts, "Var9", "EmptyFieldRule", "auto");
+
+% Import the data
+groundtruth = readtable(fileName, opts);
+
+% Initialize the output
+camPoses = repmat(rigidtform3d, 1, numel(imds.Files));
+
+firstT = [groundtruth(1,:).tx groundtruth(1,:).ty groundtruth(1,:).tz];
+firstR = quat2rotm([groundtruth(1,:).qw groundtruth(1,:).qx groundtruth(1,:).qy groundtruth(1,:).qz]);
+
+% Find the ground truth data corresponding to the image based on the timestamp 
+[~,imageTS] = fileparts(imds.Files);
+imgTimestamp = str2double(imageTS);
+index = interp1(groundtruth.timestamp, 1:numel(groundtruth.timestamp), imgTimestamp, 'nearest', 'extrap');
+
+for i=1:numel(imds.Files)
+    groundtruth_raw = groundtruth(index(i),:);
+
+    % Transform all the camera poses to the coordinate system of the first camera
+    % Rotation
+    q = [groundtruth_raw.qw groundtruth_raw.qx groundtruth_raw.qy groundtruth_raw.qz];
+    camPoses(i).R = firstR'*quat2rotm(q);
+    
+    % Translation
+    camPoses(i).Translation = ([groundtruth_raw.tx groundtruth_raw.ty groundtruth_raw.tz]-firstT) * firstR;
+end
+end
+
diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperMonoVisualSLAM.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperMonoVisualSLAM.m
new file mode 100644
index 0000000000000000000000000000000000000000..24abc6bc55ccf40ce6a91a017d17b88e0ec1d499
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperMonoVisualSLAM.m
@@ -0,0 +1,31 @@
+function [xyzPoint, camPoses] = helperMonoVisualSLAM(image)
+
+%   Copyright 2023 The MathWorks Inc.
+
+%#codegen
+
+persistent vslam xyzPointsInternal camPosesInternal
+
+if isempty(vslam)
+    % Create a monovslam class to process the image data
+    focalLength    = [535.4, 539.2];    % in units of pixels
+    principalPoint = [320.1, 247.6];    % in units of pixels
+    imageSize      = [480,     640];    % in units of pixels
+    intrinsics     = cameraIntrinsics(focalLength, principalPoint, imageSize);
+
+    vslam = monovslam(intrinsics);
+end
+
+% Process each image frame
+addFrame(vslam, image);
+
+% Get 3-D map points and camera poses
+if isempty(xyzPointsInternal) || hasNewKeyFrame(vslam)
+    xyzPointsInternal = mapPoints(vslam);
+    camPosesInternal = poses(vslam);
+end
+
+xyzPoint = xyzPointsInternal;
+
+% Convert camera poses to homogeneous transformation matrices
+camPoses = cat(3, camPosesInternal.A);
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperORBFeatureExtractorFunction.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperORBFeatureExtractorFunction.m
new file mode 100644
index 0000000000000000000000000000000000000000..d8c77bf675b0e62057d8b72b15581914ba951f22
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperORBFeatureExtractorFunction.m
@@ -0,0 +1,25 @@
+function [features, featureMetrics]= helperORBFeatureExtractorFunction(I)
+% helperORBFeatureExtractorFunction Implements the ORB feature extraction 
+% used in bagOfFeatures.
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2021 The MathWorks, Inc.
+
+numPoints   = 1000;
+
+% Detect ORB features
+Igray  = im2gray(I);
+
+points = detectORBFeatures(Igray, 'ScaleFactor', 1.2, 'NumLevels', 8);
+
+% Select a subset of features, uniformly distributed throughout the image
+points = selectUniform(points, numPoints, size(Igray, 1:2));
+
+% Extract features
+features = extractFeatures(Igray, points);
+
+% Compute the Feature Metric. Use the variance of features as the metric
+featureMetrics = var(single(features.Features),[],2);
+
diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLastKeyFrame.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLastKeyFrame.m
new file mode 100644
index 0000000000000000000000000000000000000000..467ff8188bc13a55f385e8062267d67f5d77ff54
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLastKeyFrame.m
@@ -0,0 +1,106 @@
+%helperTrackLastKeyFrame Estimate the camera pose by tracking the last key frame
+%   [currPose, mapPointIdx, featureIdx] = helperTrackLastKeyFrameStereo(mapPoints, 
+%   views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor) estimates
+%   the camera pose of the current frame by matching features with the
+%   previous key frame.
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+%
+%   Inputs
+%   ------
+%   mapPoints         - A helperMapPoints objects storing map points
+%   views             - View attributes of key frames
+%   currFeatures      - Features in the current frame 
+%   currPoints        - Feature points in the current frame                 
+%   lastKeyFrameId    - ViewId of the last key frame 
+%   intrinsics        - Camera intrinsics 
+%   scaleFactor       - scale factor of features
+%   
+%   Outputs
+%   -------
+%   currPose          - Estimated camera pose of the current frame
+%   mapPointIdx       - Indices of map points observed in the current frame
+%   featureIdx        - Indices of features corresponding to mapPointIdx
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+function [currPose, mapPointIdx, featureIdx] = helperTrackLastKeyFrame(...
+    mapPoints, views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor)
+
+% Match features from the previous key frame with known world locations
+[index3d, index2d]    = findWorldPointsInView(mapPoints, lastKeyFrameId);
+lastKeyFrameFeatures  = views.Features{lastKeyFrameId}(index2d,:);
+lastKeyFramePoints    = views.Points{lastKeyFrameId}(index2d);
+
+indexPairs  = matchFeatures(currFeatures, binaryFeatures(lastKeyFrameFeatures),...
+    'Unique', true, 'MaxRatio', 0.9, 'MatchThreshold', 40);
+
+% Estimate the camera pose
+matchedImagePoints = currPoints.Location(indexPairs(:,1),:);
+matchedWorldPoints = mapPoints.WorldPoints(index3d(indexPairs(:,2)), :);
+
+matchedImagePoints = cast(matchedImagePoints, 'like', matchedWorldPoints);
+[currPose, inlier, status] = estworldpose(...
+    matchedImagePoints, matchedWorldPoints, intrinsics, ...
+    'Confidence', 95, 'MaxReprojectionError', 3, 'MaxNumTrials', 1e4);
+
+if status
+    currPose=[];
+    mapPointIdx=[];
+    featureIdx=[];
+    return
+end
+
+% Refine camera pose only
+currPose = bundleAdjustmentMotion(matchedWorldPoints(inlier,:), ...
+    matchedImagePoints(inlier,:), currPose, intrinsics, ...
+    'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,...
+    'RelativeTolerance', 1e-15, 'MaxIteration', 20);
+
+% Search for more matches with the map points in the previous key frame
+xyzPoints = mapPoints.WorldPoints(index3d,:);
+
+[projectedPoints, isInImage] = world2img(xyzPoints, pose2extr(currPose), intrinsics);
+projectedPoints = projectedPoints(isInImage, :);
+
+minScales    = max(1, lastKeyFramePoints.Scale(isInImage)/scaleFactor);
+maxScales    = lastKeyFramePoints.Scale(isInImage)*scaleFactor;
+r            = 4;
+searchRadius = r*lastKeyFramePoints.Scale(isInImage);
+
+indexPairs   = matchFeaturesInRadius(binaryFeatures(lastKeyFrameFeatures(isInImage,:)), ...
+    binaryFeatures(currFeatures.Features), currPoints, projectedPoints, searchRadius, ...
+    'MatchThreshold', 40, 'MaxRatio', 0.8, 'Unique', true);
+
+if size(indexPairs, 1) < 20
+    indexPairs   = matchFeaturesInRadius(binaryFeatures(lastKeyFrameFeatures(isInImage,:)), ...
+        binaryFeatures(currFeatures.Features), currPoints, projectedPoints, 2*searchRadius, ...
+        'MatchThreshold', 40, 'MaxRatio', 1, 'Unique', true);
+end
+
+if size(indexPairs, 1) < 10
+    currPose=[];
+    mapPointIdx=[];
+    featureIdx=[];
+    return
+end
+
+% Filter by scales
+isGoodScale = currPoints.Scale(indexPairs(:, 2)) >= minScales(indexPairs(:, 1)) & ...
+    currPoints.Scale(indexPairs(:, 2)) <= maxScales(indexPairs(:, 1));
+indexPairs  = indexPairs(isGoodScale, :);
+
+% Obtain the index of matched map points and features
+tempIdx            = find(isInImage); % Convert to linear index
+mapPointIdx        = index3d(tempIdx(indexPairs(:,1)));
+featureIdx         = indexPairs(:,2);
+
+% Refine the camera pose again
+matchedWorldPoints = mapPoints.WorldPoints(mapPointIdx, :);
+matchedImagePoints = currPoints.Location(featureIdx, :);
+
+currPose = bundleAdjustmentMotion(matchedWorldPoints, matchedImagePoints, ...
+    currPose, intrinsics, 'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,...
+    'RelativeTolerance', 1e-15, 'MaxIteration', 20);
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLocalMap.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLocalMap.m
new file mode 100644
index 0000000000000000000000000000000000000000..d64da7a28ae032e7fd6db8a0e0b689a2c90d06a6
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperTrackLocalMap.m
@@ -0,0 +1,221 @@
+function [localKeyFrameIds, currPose, mapPointIdx, featureIdx, isKeyFrame] = ...
+    helperTrackLocalMap(mapPoints, vSetKeyFrames, mapPointIdx, ...
+    featureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ...
+    newKeyFrameAdded, lastKeyFrameIndex, currFrameIndex, numSkipFrames, numPointsKeyFrame)
+%helperTrackLocalMap Refine camera pose by tracking the local map
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+%
+%   Inputs
+%   ------
+%   mapPoints         - A worldpointset object storing map points
+%   vSetKeyFrames     - An imageviewset storing key frames
+%   mapPointsIndices  - Indices of map points observed in the current frame
+%   featureIndices    - Indices of features in the current frame 
+%                       corresponding to map points denoted by mapPointsIndices                      
+%   currPose          - Current camera pose
+%   currFeatures      - ORB Features in the current frame 
+%   currPoints        - Feature points in the current frame
+%   intrinsics        - Camera intrinsics 
+%   scaleFactor       - scale factor of features
+%   numLevels         - number of levels in feature exatraction
+%   newKeyFrameAdded  - A boolean scalar indicating if a new key frame is
+%                       added recently
+%   lastKeyFrameIndex - Frame index of the last key frame
+%   currFrameIndex    - Frame index of the current frame
+%   numSkipFrames     - Largest number of frames to skip
+%   numPointsKeyFrame - Minimum number of points tracked by a key frame
+%   
+%   Outputs
+%   -------
+%   localKeyFrameIds  - ViewIds of the local key frames 
+%   currPose          - Refined camera pose of the current frame
+%   mapPointIdx       - Indices of map points observed in the current frame
+%   featureIdx        - Indices of features in the current frame corresponding
+%                       to mapPointIdx
+%   isKeyFrame        - A boolean scalar indicating if the current frame is
+%                       a key frame
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+persistent numPointsRefKeyFrame localPointsIndices localKeyFrameIdsInternal
+
+if isempty(numPointsRefKeyFrame) || newKeyFrameAdded
+    [localPointsIndices, localKeyFrameIdsInternal, numPointsRefKeyFrame] = ...
+    updateRefKeyFrameAndLocalPoints(mapPoints, vSetKeyFrames, mapPointIdx);
+end
+
+% Project the map into the frame and search for more map point correspondences
+newMapPointIdx = setdiff(localPointsIndices, mapPointIdx, 'stable');
+localFeatures  = getFeatures(mapPoints, vSetKeyFrames.Views, newMapPointIdx); 
+[projectedPoints, inlierIndex, predictedScales, viewAngles] = removeOutlierMapPoints(mapPoints, ...
+    currPose, intrinsics, newMapPointIdx, scaleFactor, numLevels);
+
+newMapPointIdx = newMapPointIdx(inlierIndex);
+localFeatures  = localFeatures(inlierIndex,:);
+
+unmatchedfeatureIdx = setdiff(cast((1:size( currFeatures.Features, 1)).', 'uint32'), ...
+    featureIdx,'stable');
+unmatchedFeatures   = currFeatures.Features(unmatchedfeatureIdx, :);
+unmatchedValidPoints= currPoints(unmatchedfeatureIdx);
+
+% Search radius depends on scale and view direction
+searchRadius    = 4*ones(size(localFeatures, 1), 1);
+searchRadius(viewAngles<3) = 2.5;
+searchRadius    = searchRadius.*predictedScales;
+
+indexPairs = matchFeaturesInRadius(binaryFeatures(localFeatures),...
+    binaryFeatures(unmatchedFeatures), unmatchedValidPoints, projectedPoints, ...
+    searchRadius, 'MatchThreshold', 40, 'MaxRatio', 0.9, 'Unique', true);
+
+% Filter by scales
+isGoodScale = currPoints.Scale(indexPairs(:, 2)) >= ...
+    max(1, predictedScales(indexPairs(:, 1))/scaleFactor) & ...
+    currPoints.Scale(indexPairs(:, 2)) <= predictedScales(indexPairs(:, 1));
+indexPairs  = indexPairs(isGoodScale, :);
+
+% Refine camera pose with more 3D-to-2D correspondences
+mapPointIdx   = [newMapPointIdx(indexPairs(:,1)); mapPointIdx];
+featureIdx     = [unmatchedfeatureIdx(indexPairs(:,2)); featureIdx];
+matchedMapPoints   = mapPoints.WorldPoints(mapPointIdx,:);
+matchedImagePoints = currPoints.Location(featureIdx,:);
+
+isKeyFrame = checkKeyFrame(numPointsRefKeyFrame, lastKeyFrameIndex, ...
+    currFrameIndex, mapPointIdx, numSkipFrames, numPointsKeyFrame);
+
+localKeyFrameIds = localKeyFrameIdsInternal;
+
+if isKeyFrame
+    % Refine camera pose only if the current frame is a key frame
+    currPose = bundleAdjustmentMotion(matchedMapPoints, matchedImagePoints, ...
+        currPose, intrinsics, 'PointsUndistorted', true, ...
+        'AbsoluteTolerance', 1e-7, 'RelativeTolerance', 1e-16,'MaxIteration', 20);
+end
+end
+
+function [localPointsIndices, localKeyFrameIds, numPointsRefKeyFrame] = ...
+    updateRefKeyFrameAndLocalPoints(mapPoints, vSetKeyFrames, pointIndices)
+
+if vSetKeyFrames.NumViews == 1
+    localKeyFrameIds = vSetKeyFrames.Views.ViewId;
+    localPointsIndices = (1:mapPoints.Count)';
+    numPointsRefKeyFrame = mapPoints.Count;
+    return
+end
+
+% The reference key frame has the most covisible map points 
+viewIds = findViewsOfWorldPoint(mapPoints, pointIndices);
+refKeyFrameId = mode(vertcat(viewIds{:}));
+
+localKeyFrames = connectedViews(vSetKeyFrames, refKeyFrameId, "MaxDistance", 2);
+localKeyFrameIds = [localKeyFrames.ViewId; refKeyFrameId];
+
+pointIdx = findWorldPointsInView(mapPoints, localKeyFrameIds);
+if iscell(pointIdx)
+    numPointsRefKeyFrame = numel(pointIdx{localKeyFrameIds==refKeyFrameId});
+    localPointsIndices = sort(vertcat(pointIdx{:}));
+else
+    numPointsRefKeyFrame = numel(pointIdx);
+    localPointsIndices = sort(pointIdx);
+end
+end
+
+function features = getFeatures(mapPoints, views, mapPointIdx)
+
+% Efficiently retrieve features and image points corresponding to map points
+% denoted by mapPointIdx
+allIndices = zeros(1, numel(mapPointIdx));
+
+% ViewId and offset pair
+count = []; % (ViewId, NumFeatures)
+viewsFeatures = views.Features;
+
+for i = 1:numel(mapPointIdx)
+    index3d  = mapPointIdx(i);
+    
+    viewId   = double(mapPoints.RepresentativeViewId(index3d));
+    
+    if isempty(count)
+        count = [viewId, size(viewsFeatures{viewId},1)];
+    elseif ~any(count(:,1) == viewId)
+        count = [count; viewId, size(viewsFeatures{viewId},1)];
+    end
+    
+    idx = find(count(:,1)==viewId);
+    
+    if idx > 1
+        offset = sum(count(1:idx-1,2));
+    else
+        offset = 0;
+    end
+    allIndices(i) = mapPoints.RepresentativeFeatureIndex(index3d) + offset;
+end
+
+uIds = count(:,1);
+
+% Concatenating features and indexing once is faster than accessing via a for loop
+allFeatures = vertcat(viewsFeatures{uIds});
+features    = allFeatures(allIndices, :);
+end
+
+function [projectedPoints, inliers, predictedScales, viewAngles] = removeOutlierMapPoints(...
+    mapPoints, pose, intrinsics, localPointsIndices, scaleFactor, ...
+    numLevels)
+
+% 1) Points within the image bounds
+xyzPoints = mapPoints.WorldPoints(localPointsIndices, :);
+[projectedPoints, isInImage] = world2img(xyzPoints, pose2extr(pose), intrinsics);
+
+if isempty(projectedPoints)
+    error('Tracking failed. Try inserting new key frames more frequently.')
+end
+
+% 2) Parallax less than 60 degrees
+cameraNormVector = [0 0 1] * pose.Rotation;
+cameraToPoints   = xyzPoints - pose.Translation;
+viewDirection    = mapPoints.ViewingDirection(localPointsIndices, :);
+validByView      = sum(viewDirection.*cameraToPoints, 2) > ...
+    cosd(60)*(vecnorm(cameraToPoints, 2, 2));
+
+% 3) Distance from map point to camera center is in the range of scale
+% invariant depth
+minDist          = mapPoints.DistanceLimits(localPointsIndices,1)/scaleFactor;
+maxDist          = mapPoints.DistanceLimits(localPointsIndices,2)*scaleFactor;
+dist             = vecnorm(xyzPoints - pose.Translation, 2, 2);
+
+validByDistance  = dist > minDist & dist < maxDist;
+
+inliers          = isInImage & validByView & validByDistance;
+
+% Predicted scales
+level= ceil(log(maxDist ./ dist)./log(scaleFactor));
+level(level<0)   = 0;
+level(level>=numLevels-1) = numLevels-1;
+predictedScales  = scaleFactor.^level;
+
+% View angles
+viewAngles       = acosd(sum(cameraNormVector.*cameraToPoints, 2) ./ ...
+    vecnorm(cameraToPoints, 2, 2));
+
+predictedScales  = predictedScales(inliers);
+viewAngles       = viewAngles(inliers);
+
+projectedPoints = projectedPoints(inliers, :);
+end
+
+function isKeyFrame = checkKeyFrame(numPointsRefKeyFrame, lastKeyFrameIndex, ...
+    currFrameIndex, mapPointsIndices, numSkipFrames, numPointsKeyFrame)
+
+% More than numSkipFrames frames have passed from last key frame insertion
+tooManyNonKeyFrames = currFrameIndex > lastKeyFrameIndex + numSkipFrames;
+
+% Track less than numPointsKeyFrame map points
+tooFewMapPoints     = numel(mapPointsIndices) < numPointsKeyFrame;
+
+% Tracked map points are fewer than 90% of points tracked by
+% the reference key frame
+tooFewTrackedPoints = numel(mapPointsIndices) < 0.9 * numPointsRefKeyFrame;
+
+isKeyFrame = (tooManyNonKeyFrames || tooFewMapPoints) && tooFewTrackedPoints;
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMatchedFeatures.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMatchedFeatures.m
new file mode 100644
index 0000000000000000000000000000000000000000..ff223197e98f091b99e2d4ea5cb42411f276b9c3
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMatchedFeatures.m
@@ -0,0 +1,50 @@
+classdef helperVisualizeMatchedFeatures < handle
+%helperVisualizeMatchedFeatures show the matched features in a frame
+%
+%   This is an example helper class that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2019-2020 The MathWorks, Inc.
+
+    properties (Access = private)
+        Image
+        
+        Feature
+    end
+    
+    methods (Access = public)
+        
+        function obj = helperVisualizeMatchedFeatures(I, featurePoints)
+            locations= featurePoints.Location;
+            
+            % Plot image
+            hFig  = figure;
+            hAxes = newplot(hFig); 
+            
+            % Set figure visibility and position
+            hFig.Visible = 'on';
+            movegui(hFig, [300 220]);
+            
+            % Show the image
+            obj.Image = imshow(I, 'Parent', hAxes, 'Border', 'tight');
+            title(hAxes, 'Matched Features in Current Frame');
+            hold(hAxes, 'on');
+            
+            % Plot features
+            plot(featurePoints, hAxes, 'ShowOrientation',false, ...
+                'ShowScale',false);
+            obj.Feature = findobj(hAxes.Parent,'Type','Line'); 
+        end 
+        
+        function updatePlot(obj, I, featurePoints)
+            locations = featurePoints.Location;
+            obj.Image.CData   = I;
+            obj.Feature.XData = locations(:,1);
+            obj.Feature.YData = locations(:,2);
+            drawnow limitrate
+        end
+    end
+end
+
+
+
diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMotionAndStructure.m b/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMotionAndStructure.m
new file mode 100644
index 0000000000000000000000000000000000000000..b064c0480c02a1f23f6c64ff7d6a4dfe3c723953
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_Example/helperVisualizeMotionAndStructure.m
@@ -0,0 +1,156 @@
+classdef helperVisualizeMotionAndStructure < handle
+%helperVisualizeMatchedFeatures show map points and camera trajectory
+%
+%   This is an example helper class that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+    properties
+        XLim = [-1.5 1.5]
+        
+        YLim = [-1 0.5]
+        
+        ZLim = [-0.5 2]
+        
+        Axes
+    end
+    
+    properties (Access = private)
+        MapPointsPlot
+ 
+        EstimatedTrajectory
+        
+        OptimizedTrajectory
+
+        CameraPlot
+    end
+
+    methods (Access = public)
+        function obj = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPoints, varargin)
+
+            if nargin > 2
+                obj.XLim = varargin{1};
+                obj.YLim = varargin{2};
+                obj.ZLim = varargin{3};
+            end
+        
+            [xyzPoints, currPose, trajectory]  = retrievePlottedData(obj, vSetKeyFrames, mapPoints);
+             
+            obj.MapPointsPlot = pcplayer(obj.XLim, obj.YLim, obj.ZLim, ...
+                'VerticalAxis', 'y', 'VerticalAxisDir', 'down');
+            
+            obj.Axes  = obj.MapPointsPlot.Axes;
+            obj.MapPointsPlot.view(xyzPoints); 
+            obj.Axes.Children.DisplayName = 'Map points';
+            
+            hold(obj.Axes, 'on');
+            
+            % Set figure position on the screen
+            movegui(obj.Axes.Parent, [1000 200]);
+            
+            % Plot camera trajectory
+            obj.EstimatedTrajectory = plot3(obj.Axes, trajectory(:,1), trajectory(:,2), ...
+                trajectory(:,3), 'r', 'LineWidth', 2 , 'DisplayName', 'Estimated trajectory');
+            
+            % Plot the current cameras
+            obj.CameraPlot = plotCamera(currPose, 'Parent', obj.Axes, 'Size', 0.05);
+        end
+        
+        function updatePlot(obj, vSetKeyFrames, mapPoints)
+            
+            [xyzPoints, currPose, trajectory]  = retrievePlottedData(obj, vSetKeyFrames, mapPoints);
+            
+            % Update the point cloud
+            obj.MapPointsPlot.view(xyzPoints);
+            
+            % Update the camera trajectory
+            set(obj.EstimatedTrajectory, 'XData', trajectory(:,1), 'YData', ...
+                trajectory(:,2), 'ZData', trajectory(:,3));
+            
+            % Update the current camera pose since the first camera is fixed
+            obj.CameraPlot.AbsolutePose = currPose.AbsolutePose;
+            obj.CameraPlot.Label        = num2str(currPose.ViewId);
+            
+            drawnow limitrate
+        end
+        
+        function plotOptimizedTrajectory(obj, poses)
+            
+            % Delete the camera plot
+            delete(obj.CameraPlot);
+            
+            % Plot the optimized trajectory
+            trans = vertcat(poses.AbsolutePose.Translation);
+            obj.OptimizedTrajectory = plot3(obj.Axes, trans(:, 1), trans(:, 2), trans(:, 3), 'm', ...
+                'LineWidth', 2, 'DisplayName', 'Optimized trajectory');
+        end
+        
+        function plotActualTrajectory(obj, gTruth, optimizedPoses)
+            estimatedCams = vertcat(optimizedPoses.AbsolutePose.Translation);
+            actualCams    = vertcat(gTruth.Translation);
+            scale = median(vecnorm(actualCams, 2, 2))/ median(vecnorm(estimatedCams, 2, 2));
+            
+            % Update the plot based on the ground truth
+            updatePlotScale(obj, scale);
+            
+            % Plot the ground truth
+            plot3(obj.Axes, actualCams(:,1), actualCams(:,2), actualCams(:,3), ...
+                'g','LineWidth',2, 'DisplayName', 'Actual trajectory');
+            
+            drawnow limitrate
+        end
+        
+        function showLegend(obj)
+            % Add a legend to the axes
+            hLegend = legend(obj.Axes, 'Location',  'northeast', ...
+                'TextColor', [1 1 1], 'FontWeight', 'bold');
+        end
+    end
+    
+    methods (Access = private)
+        function [xyzPoints, currPose, trajectory]  = retrievePlottedData(obj, vSetKeyFrames, mapPoints)
+            camPoses    = poses(vSetKeyFrames);
+            currPose    = camPoses(end,:); % Contains both ViewId and Pose
+
+            % Ensure the rotation matrix is a rigid transformation
+            R = double(currPose.AbsolutePose.R);
+            t = double(currPose.AbsolutePose.Translation);
+            [U, ~, V] = svd(R);
+            currPose.AbsolutePose.A = eye(4);
+            currPose.AbsolutePose.A(1:3, 4) = t;
+            currPose.AbsolutePose.A(1:3, 1:3) = U * V';
+
+            trajectory  = vertcat(camPoses.AbsolutePose.Translation);
+            xyzPoints   = mapPoints.WorldPoints;
+            
+            % Only plot the points within the limit
+            inPlotRange = xyzPoints(:, 1) > obj.XLim(1) & ...
+                xyzPoints(:, 1) < obj.XLim(2) & xyzPoints(:, 2) > obj.YLim(1) & ...
+                xyzPoints(:, 2) < obj.YLim(2) & xyzPoints(:, 3) > obj.ZLim(1) & ...
+                xyzPoints(:, 3) < obj.ZLim(2);
+            xyzPoints   = xyzPoints(inPlotRange, :);
+        end
+        
+        function updatePlotScale(obj, scale)
+            % Update the map points and camera trajectory based on the
+            % ground truth scale
+            obj.Axes.XLim = obj.Axes.XLim * scale;
+            obj.Axes.YLim = obj.Axes.YLim * scale;
+            obj.Axes.ZLim = obj.Axes.ZLim * scale;
+            
+            % Map points
+            obj.Axes.Children(end).XData = obj.Axes.Children(end).XData * scale;
+            obj.Axes.Children(end).YData = obj.Axes.Children(end).YData * scale;
+            obj.Axes.Children(end).ZData = obj.Axes.Children(end).ZData * scale;
+            
+            % Estiamted and optimized Camera trajectory
+            obj.EstimatedTrajectory.XData =  obj.EstimatedTrajectory.XData * scale;
+            obj.EstimatedTrajectory.YData =  obj.EstimatedTrajectory.YData * scale;
+            obj.EstimatedTrajectory.ZData =  obj.EstimatedTrajectory.ZData * scale;
+            obj.OptimizedTrajectory.XData =  obj.OptimizedTrajectory.XData * scale;
+            obj.OptimizedTrajectory.YData =  obj.OptimizedTrajectory.YData * scale;
+            obj.OptimizedTrajectory.ZData =  obj.OptimizedTrajectory.ZData * scale;
+        end
+    end
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_Example/orbslamGroundTruth.mat b/target/classes/vslam/Mathworks_VSLAM_Example/orbslamGroundTruth.mat
new file mode 100644
index 0000000000000000000000000000000000000000..ea1360e39c14cb70268bf6d6d4202b51eaf02014
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diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/VisualSLAMWithAnRGBDCameraExample.mlx b/target/classes/vslam/Mathworks_VSLAM_RGBD/VisualSLAMWithAnRGBDCameraExample.mlx
new file mode 100644
index 0000000000000000000000000000000000000000..b2a042f3ed3d1de4c0281552531e4780e2c16187
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diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/bagOfFeaturesDataSLAM.mat b/target/classes/vslam/Mathworks_VSLAM_RGBD/bagOfFeaturesDataSLAM.mat
new file mode 100644
index 0000000000000000000000000000000000000000..bba0c9c9f9fced2771381f71adc28636701665c9
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diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddLoopConnectionsStereo.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddLoopConnectionsStereo.m
new file mode 100644
index 0000000000000000000000000000000000000000..5ddcc506b3caa8b678b41692fdd27289826c70d7
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddLoopConnectionsStereo.m
@@ -0,0 +1,81 @@
+function [isLoopClosed, mapPoints, vSetKeyFrames] = helperAddLoopConnectionsStereo(...
+    mapPoints, vSetKeyFrames, loopCandidates, currKeyFrameId, currFeatures, ...
+    currPoints, loopEdgeNumMatches, varargin)
+%helperAddLoopConnectionsStereo add connections between the current key frame and
+%   the valid loop candidate key frames. A loop candidate is valid if it has
+%   enough covisible map points with the current key frame.
+
+%   This is an example helper function that is subject to change or removal
+%   in future releases.
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+if nargin > 7
+    maxDistance = varargin{1};
+else
+    maxDistance = 4;
+end
+
+loopClosureEdge = [];
+
+numCandidates   = size(loopCandidates,2);
+[index3d1, index2d1] = findWorldPointsInView(mapPoints, currKeyFrameId);
+validFeatures1  = currFeatures.Features(index2d1, :);
+validPoints1    = currPoints(index2d1, :);
+
+for k = 1 : numCandidates
+    [index3d2, index2d2] = findWorldPointsInView(mapPoints, loopCandidates(k));
+    allFeatures2   = vSetKeyFrames.Views.Features{loopCandidates(k)};
+    allPoints2     = vSetKeyFrames.Views.Points{loopCandidates(k)};
+    validFeatures2 = allFeatures2(index2d2, :);
+    validPoints2   = allPoints2(index2d2, :);
+    
+    indexPairs = matchFeatures(binaryFeatures(validFeatures1), binaryFeatures(validFeatures2), ...
+        'Unique', true, 'MaxRatio', 0.9, 'MatchThreshold', 40);
+    
+    % Orientation consistency check
+    orientation1 = validPoints1.Orientation(indexPairs(:,1));
+    orientation2 = validPoints2.Orientation(indexPairs(:,2));
+    [N, ~, bin] = histcounts(abs(orientation1 - orientation2), 0:pi/30:2*pi);
+    [~, ia] = maxk(N, 3); % Select the top 3 bins
+    isConsistent = ismember(bin, ia);
+
+    indexPairs = indexPairs(isConsistent, :);
+
+    % Check if all the candidate key frames have strong connection with the
+    % current keyframe
+    if size(indexPairs, 1) < loopEdgeNumMatches
+        continue
+    end
+    
+    % Estimate the relative pose of the current key frame with respect to the
+    % loop candidate keyframe with the highest similarity score
+    
+    worldPoints1 = mapPoints.WorldPoints(index3d1(indexPairs(:, 1)), :);
+    worldPoints2 = mapPoints.WorldPoints(index3d2(indexPairs(:, 2)), :);
+
+    tform1 = pose2extr(vSetKeyFrames.Views.AbsolutePose(end));
+    tform2 = pose2extr(vSetKeyFrames.Views.AbsolutePose(loopCandidates(k)));
+
+    worldPoints1InCamera1 = transformPointsForward(tform1, worldPoints1); 
+    worldPoints2InCamera2 = transformPointsForward(tform2, worldPoints2); 
+    
+    w = warning('off','all');
+    [tform, inlierIndex] = estgeotform3d(worldPoints1InCamera1, ...
+        worldPoints2InCamera2, 'rigid', 'MaxNumTrials', 1e4, 'MaxDistance', maxDistance);
+    warning(w);
+
+    % Add connection between the current key frame and the loop key frame
+    matches = uint32([index2d2(indexPairs(inlierIndex, 2)), index2d1(indexPairs(inlierIndex, 1))]);
+    vSetKeyFrames = addConnection(vSetKeyFrames, loopCandidates(k), currKeyFrameId, tform, 'Matches', matches);
+    disp(['Loop edge added between keyframe: ', num2str(loopCandidates(k)), ' and ', num2str(currKeyFrameId)]);
+    
+    % Fuse co-visible map points
+    matchedIndex3d1 = index3d1(indexPairs(inlierIndex, 1));
+    matchedIndex3d2 = index3d2(indexPairs(inlierIndex, 2));
+    mapPoints = updateWorldPoints(mapPoints, matchedIndex3d1, mapPoints.WorldPoints(matchedIndex3d2, :));
+    
+    loopClosureEdge = [loopClosureEdge; loopCandidates(k), currKeyFrameId];
+end
+isLoopClosed = ~isempty(loopClosureEdge);
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddNewKeyFrame.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddNewKeyFrame.m
new file mode 100644
index 0000000000000000000000000000000000000000..8171da4598e2f5e654d532de5f2eafe794b88a54
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperAddNewKeyFrame.m
@@ -0,0 +1,54 @@
+function [mapPoints, vSetKeyFrames] = helperAddNewKeyFrame(mapPoints, vSetKeyFrames,...
+    cameraPose, currFeatures, currPoints, mapPointsIndices, featureIndices, keyFramesIndices)
+%helperAddNewKeyFrame add key frames to the key frame set
+%
+%   This is an example helper function that is subject to change or removal
+%   in future releases.
+
+%   Copyright 2019-2023 The MathWorks, Inc.
+%#codegen
+
+viewId = vSetKeyFrames.Views.ViewId(end)+1;
+
+vSetKeyFrames = addView(vSetKeyFrames, viewId, cameraPose,...
+    'Features', currFeatures.Features, ...
+    'Points', currPoints);
+
+viewsAbsPoses = vSetKeyFrames.Views.AbsolutePose;
+
+for i = 1:numel(keyFramesIndices)
+    localKeyFrameId = keyFramesIndices(i);
+    if isSimMode()
+        [index3d, index2d] = findWorldPointsInView(mapPoints, localKeyFrameId);
+    else
+        [index3dCg, index2dCg] = findWorldPointsInView(mapPoints, localKeyFrameId);
+        index3d = index3dCg{1};
+        index2d = index2dCg{1};
+    end
+    [~, ia, ib] = intersect(index3d, mapPointsIndices, 'stable');
+
+    prePose   = viewsAbsPoses(localKeyFrameId);
+    relPose = rigidtform3d(prePose.R' * cameraPose.R, ...
+        (cameraPose.Translation-prePose.Translation)*prePose.R);
+
+    if numel(ia) > 5
+        if isSimMode()
+            vSetKeyFrames = addConnection(vSetKeyFrames, localKeyFrameId, viewId, relPose, ...
+                'Matches', [index2d(ia),featureIndices(ib)]);
+        else
+            coder.varsize('matches', [inf 2], [1, 0]);
+            fIndices = featureIndices(ib(:));
+            matches = [index2d(ia), fIndices];
+            vSetKeyFrames = addConnection(vSetKeyFrames, localKeyFrameId, viewId, relPose, ...
+                'Matches', matches);
+        end
+    end
+end
+
+mapPoints = addCorrespondences(mapPoints, viewId, mapPointsIndices, ...
+    featureIndices);
+end
+
+function tf = isSimMode()
+    tf = isempty(coder.target);
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCheckLoopClosure.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCheckLoopClosure.m
new file mode 100644
index 0000000000000000000000000000000000000000..7cff3e85c2f308126c160e6d73176923a5b38914
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCheckLoopClosure.m
@@ -0,0 +1,58 @@
+function [isDetected, loopKeyFrameIds] = helperCheckLoopClosure(vSetKeyFrames, ...
+    currKeyframeId, imageDatabase, currImg, loopEdgeNumMatches)
+%helperCheckLoopClosure detect loop candidates key frames by retrieving
+%   visually similar images from the feature database.
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2019-2023 The MathWorks, Inc.
+%#codegen
+
+% Retrieve all the visually similar key frames
+[candidateViewIds, similarityscores] = retrieveImages(currImg, imageDatabase);
+
+% Compute similarity between the current key frame and its strongly-connected 
+% key frames. The minimum similarity score is used as a baseline to find 
+% loop candidate key frames, which are visually similar to but not connected 
+% to the current key frame
+covisViews          = connectedViews(vSetKeyFrames, currKeyframeId);
+covisViewsIds       = covisViews.ViewId;
+strongCovisViews    = connectedViews(vSetKeyFrames, currKeyframeId, 'MinNumMatches', loopEdgeNumMatches);
+strongCovisViewIds  = strongCovisViews.ViewId;
+
+% Retrieve the top 10 similar connected key frames
+[~,~,scores] = evaluateImageRetrieval(currImg, imageDatabase, strongCovisViewIds, 'NumResults', 10);
+minScore     = min(scores);
+
+[loopKeyFrameIds,ia] = setdiff(candidateViewIds, covisViewsIds, 'stable');
+
+% Scores of non-connected key frames
+candidateScores  = similarityscores(ia); % Descending
+
+if ~isempty(ia)
+    bestScore       = candidateScores(1);
+    
+    % Score must be higher than the 75% of the best score 
+    isValid         = candidateScores > max(bestScore*0.75, minScore);
+    
+    loopKeyFrameIds = loopKeyFrameIds(isValid);
+else
+    loopKeyFrameIds = zeros(coder.ignoreConst(0), coder.ignoreConst(0), class(loopKeyFrameIds));
+end
+
+% Loop candidates need to be consecutively detected
+minNumCandidates = 3; % At least 3 candidates are found
+if size(loopKeyFrameIds,1) >= minNumCandidates
+    groups = nchoosek(loopKeyFrameIds, minNumCandidates);
+    consecutiveGroups = groups(max(groups,[],2) - min(groups,[],2) < 4, :);
+    if ~isempty(consecutiveGroups) % Consecutive candidates are found
+        loopKeyFrameIds = consecutiveGroups(1,:);
+        isDetected = true;
+    else
+        isDetected = false;
+    end
+else
+    isDetected = false;
+end
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCreateNewMapPointsStereo.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCreateNewMapPointsStereo.m
new file mode 100644
index 0000000000000000000000000000000000000000..c66582c070cc9b01fcf8964b53f70b124810d02d
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperCreateNewMapPointsStereo.m
@@ -0,0 +1,257 @@
+function [mapPoints, vSetKeyFrames, recentPointIdx, stereoMapPointsIndices] = helperCreateNewMapPointsStereo(...
+    mapPoints, vSetKeyFrames, currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax, ...
+    unmatchedFeatureIdx, stereoMapPointsIndices)
+%helperCreateNewMapPointsStereo creates new map points by triangulating matched
+%   feature points in the current key frame and the connected key frames.
+%
+%   This is an example helper function that is subject to change or removal
+%   in future releases.
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+% Get connected key frames
+KcViews  = connectedViews(vSetKeyFrames, currKeyFrameId, minNumMatches);
+KcIDs    = KcViews.ViewId;
+
+% Retreive data of the current key frame
+currPose        = vSetKeyFrames.Views.AbsolutePose(currKeyFrameId);
+currFeatures    = vSetKeyFrames.Views.Features{currKeyFrameId};
+currPoints      = vSetKeyFrames.Views.Points{currKeyFrameId};
+currLocations   = currPoints.Location;
+currScales      = currPoints.Scale;
+
+% Camera projection matrix
+currCamMatrix   = cameraProjection(intrinsics, pose2extr(currPose));
+
+recentPointIdx  = [];
+
+for i = numel(KcIDs):-1:1
+    
+    kfPose      = vSetKeyFrames.Views.AbsolutePose(KcIDs(i));
+    [~, kfIndex2d] = findWorldPointsInView(mapPoints, KcIDs(i));
+        kfCamMatrix = cameraProjection(intrinsics, pose2extr(kfPose));
+    
+    % Skip the key frame is the change of view is small
+    isViewClose = norm(kfPose.Translation - currPose.Translation) < 0.2; %baseline
+    if isViewClose
+        continue
+    end
+    
+    % Retrieve data of the connected key frame
+    kfFeatures  = vSetKeyFrames.Views.Features{KcIDs(i)};
+    kfPoints    = vSetKeyFrames.Views.Points{KcIDs(i)};
+    kfLocations = kfPoints.Location;
+    kfScales    = kfPoints.Scale;
+    
+    % currIndex2d changes in each iteration as new map points are created
+    [~, currIndex2d] = findWorldPointsInView(mapPoints, currKeyFrameId);
+    
+    % Only use unmatched feature points
+    uIndices1   = setdiff(uint32(1:size(kfFeatures,1))',  kfIndex2d);
+    uIndices2   = [setdiff(uint32(1:size(currFeatures,1))', currIndex2d); unmatchedFeatureIdx];
+    
+    uFeatures1  = kfFeatures(uIndices1, :);
+    uFeatures2  = currFeatures(uIndices2, :);
+    
+    uLocations1 = kfLocations(uIndices1, :);
+    uLocations2 = currLocations(uIndices2, :);
+    
+    uScales1    = kfScales(uIndices1);
+    uScales2    = currScales(uIndices2);
+    
+    indexPairs  = matchFeatures(binaryFeatures(uFeatures1), binaryFeatures(uFeatures2),...
+        'Unique', true, 'MaxRatio', 0.7, 'MatchThreshold', 40);
+    
+    if isempty(indexPairs)
+        continue
+    end
+    
+    % Created from stereo
+    [~, ia, ib] = intersect(unmatchedFeatureIdx, uIndices2(indexPairs(:, 2)));
+    
+    isNewPointStereo = ~isempty(ia);
+    
+    if isNewPointStereo
+        sIndices1 = uIndices1(indexPairs(ib, 1));
+        sIndices2 = unmatchedFeatureIdx(ia);
+        
+        % Update the indices
+        unmatchedFeatureIdx = setdiff(unmatchedFeatureIdx, sIndices2);
+        
+        % Filtering by view direction and reprojection error
+        xyzPoints = mapPoints.WorldPoints(stereoMapPointsIndices(ia), :);
+        
+        % Compute reprojection errors
+        [points1proj, isInFrontOfCam1] = projectPoints(xyzPoints, kfCamMatrix);
+        [points2proj, isInFrontOfCam2] = projectPoints(xyzPoints, currCamMatrix);
+        points1 = uLocations1(indexPairs(ib, 1), :)';
+        points2 = uLocations2(indexPairs(ib, 2), :)';
+        errors1 = hypot(points1(1,:)-points1proj(1,:), ...
+            points1(2,:) - points1proj(2,:));
+        errors2 = hypot(points2(1,:)-points2proj(1,:), ...
+            points2(2,:) - points2proj(2,:));
+        
+        reprojectionErrors = mean([errors1; errors2])';
+        
+        isValid = checkEpipolarConstraint(intrinsics, currPose, kfPose, points1', points2', indexPairs(ib, :), uScales2);
+        
+        validIdx = isInFrontOfCam1 & isInFrontOfCam2 & isValid;
+        
+        inlier = filterTriangulatedMapPoints(xyzPoints, kfPose, currPose, ...
+            uScales1(indexPairs(ib, 1)), uScales2(indexPairs(ib, 2)), ...
+            reprojectionErrors, scaleFactor, validIdx);
+        
+        if any(inlier)
+            mapPoints = addCorrespondences(mapPoints, KcIDs(i), stereoMapPointsIndices(ia(inlier)), sIndices1(inlier));
+            recentPointIdx = union(recentPointIdx, stereoMapPointsIndices(ia(inlier)));
+            recentPointIdx = recentPointIdx(:);
+        end
+        
+        % Created from triangulation
+        isNotPicked = true(size(indexPairs, 1), 1);
+        isNotPicked(ib(inlier)) = false;
+        indexPairs = indexPairs(isNotPicked, :);
+    end
+    
+    if isempty(indexPairs)
+        continue
+    end
+    
+    % Need to determine which way the new world points are created
+    matchedPoints1 = uLocations1(indexPairs(:,1), :);
+    matchedPoints2 = uLocations2(indexPairs(:,2), :);
+    
+    % Check epipolar constraint
+    isValid = checkEpipolarConstraint(intrinsics, currPose, kfPose, matchedPoints1, matchedPoints2, indexPairs, uScales2);
+    
+    indexPairs = indexPairs(isValid, :);
+    matchedPoints1 = matchedPoints1(isValid, :);
+    matchedPoints2 = matchedPoints2(isValid, :);
+    
+    % Parallax check
+    isLarge = isLargeParalalx(matchedPoints1, matchedPoints2, kfPose, ...
+        currPose, intrinsics, minParallax);
+    
+    matchedPoints1  = matchedPoints1(isLarge, :);
+    matchedPoints2  = matchedPoints2(isLarge, :);
+    indexPairs      = indexPairs(isLarge, :);
+    
+    % Triangulate two views to create new world points
+    [xyzPoints, reprojectionErrors, validIdx] = triangulate(matchedPoints1, ...
+        matchedPoints2, kfCamMatrix, currCamMatrix);
+    
+    % Filtering by view direction and reprojection error
+    inlier = filterTriangulatedMapPoints(xyzPoints, kfPose, currPose, ...
+        uScales1(indexPairs(:,1)), uScales2(indexPairs(:,2)), ...
+        reprojectionErrors, scaleFactor, validIdx);
+    
+    % Add new map points and update connections
+    addedMatches = [];
+    if any(inlier)
+        xyzPoints   = xyzPoints(inlier,:);
+        indexPairs  = indexPairs(inlier, :);
+        
+        mIndices1   = uIndices1(indexPairs(:, 1));
+        mIndices2   = uIndices2(indexPairs(:, 2));
+        
+        [mapPoints, indices] = addWorldPoints(mapPoints, xyzPoints);
+        recentPointIdx       = [recentPointIdx; indices]; %#ok<AGROW>
+        
+        % Add new observations
+        mapPoints  = addCorrespondences(mapPoints, KcIDs(i),indices, mIndices1);
+        mapPoints  = addCorrespondences(mapPoints, currKeyFrameId, indices, mIndices2);
+        
+        addedMatches = [mIndices1, mIndices2]; % Triangulation
+    end
+    
+    if isNewPointStereo
+        addedMatches = [sIndices1, sIndices2; addedMatches];
+    end   
+    
+    % Update connections with new feature matches
+    [~,ia]     = intersect(vSetKeyFrames.Connections{:,1:2}, ...
+        [KcIDs(i), currKeyFrameId], 'row', 'stable');
+    oldMatches = vSetKeyFrames.Connections.Matches{ia};
+    newMatches = [oldMatches; addedMatches];
+    vSetKeyFrames  = updateConnection(vSetKeyFrames, KcIDs(i), currKeyFrameId, ...
+        'Matches', newMatches);
+    
+end
+
+stereoMapPointsIndices = setdiff(stereoMapPointsIndices, recentPointIdx);
+end
+
+function F = computeF(intrinsics, pose1, pose2)
+R1 = pose1.R;
+t1 = pose1.Translation';
+
+R2 = pose2.R;
+t2 = pose2.Translation';
+
+R12 = R1'*R2;
+t12 = R1'*(t2-t1);
+
+% Skew symmetric matrix
+t12x = [0, -t12(3), t12(2)
+    t12(3), 0, -t12(1)
+    -t12(2) t12(1), 0];
+
+F = intrinsics.K'\ t12x * R12 / intrinsics.K;
+end
+
+function inlier = filterTriangulatedMapPoints(xyzPoints, pose1, pose2, ...
+    scales1, scales2, reprojectionErrors, scaleFactor, isInFront)
+
+camToPoints1= xyzPoints - pose1.Translation;
+camToPoints2= xyzPoints - pose2.Translation;
+
+% Check scale consistency and reprojection errors
+distances1  = vecnorm(camToPoints1, 2, 2);
+distances2  = vecnorm(camToPoints2, 2, 2);
+ratioDist   = distances1./distances2;
+ratioScale  = scales2./scales1;
+
+ratioFactor = 1.5 * scaleFactor;
+
+isInScale   = (ratioDist./ratioScale < ratioFactor  |  ...
+    ratioScale./ratioDist < ratioFactor);
+
+maxError    = sqrt(6);
+isSmallError= reprojectionErrors < maxError*min(scales1, scales2);
+inlier      = isInScale & isSmallError & isInFront;
+end
+
+function isLarge = isLargeParalalx(points1, points2, pose1, pose2, intrinsics, minParallax)
+
+% Parallax check
+K = intrinsics.IntrinsicMatrix;
+ray1 = [points1, ones(size(points1(:,1)))]/K *pose1.Rotation;
+ray2 = [points2, ones(size(points1(:,2)))]/K *pose2.Rotation;
+
+cosParallax = sum(ray1 .* ray2, 2) ./(vecnorm(ray1, 2, 2) .* vecnorm(ray2, 2, 2));
+isLarge     = cosParallax < cosd(minParallax) & cosParallax > 0;
+end
+
+%--------------------------------------------------------------------------
+function [points2d, isInFrontOfCamera] = projectPoints(points3d, P)
+points3dHomog = [points3d, ones(size(points3d, 1), 1, 'like', points3d)]';
+points2dHomog = P * points3dHomog;
+isInFrontOfCamera = points2dHomog(3, :)' > 0;
+points2d = bsxfun(@rdivide, points2dHomog(1:2, :), points2dHomog(3, :));
+end
+
+function isValid = checkEpipolarConstraint(intrinsics, currPose, kfPose, matchedPoints1, matchedPoints2, indexPairs, uScales2)
+% Epipole in the current key frame
+epiPole = world2img(kfPose.Translation, pose2extr(currPose), intrinsics);
+distToEpipole = vecnorm(matchedPoints2 - epiPole, 2, 2);
+
+% Compute fundamental matrix
+F = computeF(intrinsics, kfPose, currPose);
+
+% Epipolar line in the second image
+epiLine = epipolarLine(F, matchedPoints2);
+distToLine = abs(sum(epiLine.* [matchedPoints1, ones(size(matchedPoints1,1), 1)], 2))./...
+    sqrt(sum(epiLine(:,1:2).^2, 2));
+isValid = distToLine < 2*uScales2(indexPairs(:,2)) & ...
+    distToEpipole > 10*uScales2(indexPairs(:,2));
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperLocalBundleAdjustmentStereo.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperLocalBundleAdjustmentStereo.m
new file mode 100644
index 0000000000000000000000000000000000000000..1272b7951bbf8e6d80da44cd4b1a590038d46e4c
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperLocalBundleAdjustmentStereo.m
@@ -0,0 +1,49 @@
+function [mapPoints, vSetKeyFrames, newPointIdx, stereoMapPointsIndices] = helperLocalBundleAdjustmentStereo(mapPoints, ...
+    vSetKeyFrames, currKeyFrameId, intrinsics, newPointIdx, stereoMapPointsIndices)
+%helperLocalBundleAdjustmentStereo refine the pose of the current key frame and 
+%   the map of the surrrounding scene.
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2020-2022 The MathWorks, Inc.
+
+if currKeyFrameId > 2
+
+    [refinedViews, dist] = connectedViews(vSetKeyFrames, currKeyFrameId, MaxDistance=2);
+    refinedKeyFrameIds = refinedViews.ViewId;
+
+    % Always fix the first two key frames
+    fixedViewIds = refinedKeyFrameIds(dist==2);
+    fixedViewIds = fixedViewIds(1:min(10, numel(fixedViewIds)));
+
+    % Always fix the first two key frames
+    fixedViewIds = [fixedViewIds; intersect(refinedKeyFrameIds, [1 2])];
+
+    refinedKeyFrameIds = [refinedKeyFrameIds; currKeyFrameId];
+
+else
+    refinedKeyFrameIds = [1 2];
+    fixedViewIds = 1;
+end
+
+% Refine local key frames and map points
+[mapPoints, vSetKeyFrames, mapPointIdx, reprojectionErrors] = bundleAdjustment(...
+    mapPoints, vSetKeyFrames, refinedKeyFrameIds, intrinsics, 'FixedViewIDs', fixedViewIds, ...
+    'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,...
+    'RelativeTolerance', 1e-16, 'Solver', 'preconditioned-conjugate-gradient', ...
+    'MaxIteration', 10);
+
+maxError    = 6;
+isInlier    = reprojectionErrors < maxError;
+outlierIdx  = mapPointIdx(~isInlier);
+newPointIdx = setdiff(newPointIdx, outlierIdx);
+
+% Update map points and key frames
+if ~isempty(outlierIdx)
+    mapPoints = removeWorldPoints(mapPoints, outlierIdx);
+end
+
+newPointIdx = newPointIdx - arrayfun(@(x) nnz(x>outlierIdx), newPointIdx);
+stereoMapPointsIndices = stereoMapPointsIndices - arrayfun(@(x) nnz(x>outlierIdx), stereoMapPointsIndices);
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperORBFeatureExtractorFunction.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperORBFeatureExtractorFunction.m
new file mode 100644
index 0000000000000000000000000000000000000000..d8c77bf675b0e62057d8b72b15581914ba951f22
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperORBFeatureExtractorFunction.m
@@ -0,0 +1,25 @@
+function [features, featureMetrics]= helperORBFeatureExtractorFunction(I)
+% helperORBFeatureExtractorFunction Implements the ORB feature extraction 
+% used in bagOfFeatures.
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2021 The MathWorks, Inc.
+
+numPoints   = 1000;
+
+% Detect ORB features
+Igray  = im2gray(I);
+
+points = detectORBFeatures(Igray, 'ScaleFactor', 1.2, 'NumLevels', 8);
+
+% Select a subset of features, uniformly distributed throughout the image
+points = selectUniform(points, numPoints, size(Igray, 1:2));
+
+% Extract features
+features = extractFeatures(Igray, points);
+
+% Compute the Feature Metric. Use the variance of features as the metric
+featureMetrics = var(single(features.Features),[],2);
+
diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLastKeyFrame.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLastKeyFrame.m
new file mode 100644
index 0000000000000000000000000000000000000000..467ff8188bc13a55f385e8062267d67f5d77ff54
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLastKeyFrame.m
@@ -0,0 +1,106 @@
+%helperTrackLastKeyFrame Estimate the camera pose by tracking the last key frame
+%   [currPose, mapPointIdx, featureIdx] = helperTrackLastKeyFrameStereo(mapPoints, 
+%   views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor) estimates
+%   the camera pose of the current frame by matching features with the
+%   previous key frame.
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+%
+%   Inputs
+%   ------
+%   mapPoints         - A helperMapPoints objects storing map points
+%   views             - View attributes of key frames
+%   currFeatures      - Features in the current frame 
+%   currPoints        - Feature points in the current frame                 
+%   lastKeyFrameId    - ViewId of the last key frame 
+%   intrinsics        - Camera intrinsics 
+%   scaleFactor       - scale factor of features
+%   
+%   Outputs
+%   -------
+%   currPose          - Estimated camera pose of the current frame
+%   mapPointIdx       - Indices of map points observed in the current frame
+%   featureIdx        - Indices of features corresponding to mapPointIdx
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+function [currPose, mapPointIdx, featureIdx] = helperTrackLastKeyFrame(...
+    mapPoints, views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor)
+
+% Match features from the previous key frame with known world locations
+[index3d, index2d]    = findWorldPointsInView(mapPoints, lastKeyFrameId);
+lastKeyFrameFeatures  = views.Features{lastKeyFrameId}(index2d,:);
+lastKeyFramePoints    = views.Points{lastKeyFrameId}(index2d);
+
+indexPairs  = matchFeatures(currFeatures, binaryFeatures(lastKeyFrameFeatures),...
+    'Unique', true, 'MaxRatio', 0.9, 'MatchThreshold', 40);
+
+% Estimate the camera pose
+matchedImagePoints = currPoints.Location(indexPairs(:,1),:);
+matchedWorldPoints = mapPoints.WorldPoints(index3d(indexPairs(:,2)), :);
+
+matchedImagePoints = cast(matchedImagePoints, 'like', matchedWorldPoints);
+[currPose, inlier, status] = estworldpose(...
+    matchedImagePoints, matchedWorldPoints, intrinsics, ...
+    'Confidence', 95, 'MaxReprojectionError', 3, 'MaxNumTrials', 1e4);
+
+if status
+    currPose=[];
+    mapPointIdx=[];
+    featureIdx=[];
+    return
+end
+
+% Refine camera pose only
+currPose = bundleAdjustmentMotion(matchedWorldPoints(inlier,:), ...
+    matchedImagePoints(inlier,:), currPose, intrinsics, ...
+    'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,...
+    'RelativeTolerance', 1e-15, 'MaxIteration', 20);
+
+% Search for more matches with the map points in the previous key frame
+xyzPoints = mapPoints.WorldPoints(index3d,:);
+
+[projectedPoints, isInImage] = world2img(xyzPoints, pose2extr(currPose), intrinsics);
+projectedPoints = projectedPoints(isInImage, :);
+
+minScales    = max(1, lastKeyFramePoints.Scale(isInImage)/scaleFactor);
+maxScales    = lastKeyFramePoints.Scale(isInImage)*scaleFactor;
+r            = 4;
+searchRadius = r*lastKeyFramePoints.Scale(isInImage);
+
+indexPairs   = matchFeaturesInRadius(binaryFeatures(lastKeyFrameFeatures(isInImage,:)), ...
+    binaryFeatures(currFeatures.Features), currPoints, projectedPoints, searchRadius, ...
+    'MatchThreshold', 40, 'MaxRatio', 0.8, 'Unique', true);
+
+if size(indexPairs, 1) < 20
+    indexPairs   = matchFeaturesInRadius(binaryFeatures(lastKeyFrameFeatures(isInImage,:)), ...
+        binaryFeatures(currFeatures.Features), currPoints, projectedPoints, 2*searchRadius, ...
+        'MatchThreshold', 40, 'MaxRatio', 1, 'Unique', true);
+end
+
+if size(indexPairs, 1) < 10
+    currPose=[];
+    mapPointIdx=[];
+    featureIdx=[];
+    return
+end
+
+% Filter by scales
+isGoodScale = currPoints.Scale(indexPairs(:, 2)) >= minScales(indexPairs(:, 1)) & ...
+    currPoints.Scale(indexPairs(:, 2)) <= maxScales(indexPairs(:, 1));
+indexPairs  = indexPairs(isGoodScale, :);
+
+% Obtain the index of matched map points and features
+tempIdx            = find(isInImage); % Convert to linear index
+mapPointIdx        = index3d(tempIdx(indexPairs(:,1)));
+featureIdx         = indexPairs(:,2);
+
+% Refine the camera pose again
+matchedWorldPoints = mapPoints.WorldPoints(mapPointIdx, :);
+matchedImagePoints = currPoints.Location(featureIdx, :);
+
+currPose = bundleAdjustmentMotion(matchedWorldPoints, matchedImagePoints, ...
+    currPose, intrinsics, 'PointsUndistorted', true, 'AbsoluteTolerance', 1e-7,...
+    'RelativeTolerance', 1e-15, 'MaxIteration', 20);
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLocalMap.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLocalMap.m
new file mode 100644
index 0000000000000000000000000000000000000000..d64da7a28ae032e7fd6db8a0e0b689a2c90d06a6
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperTrackLocalMap.m
@@ -0,0 +1,221 @@
+function [localKeyFrameIds, currPose, mapPointIdx, featureIdx, isKeyFrame] = ...
+    helperTrackLocalMap(mapPoints, vSetKeyFrames, mapPointIdx, ...
+    featureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ...
+    newKeyFrameAdded, lastKeyFrameIndex, currFrameIndex, numSkipFrames, numPointsKeyFrame)
+%helperTrackLocalMap Refine camera pose by tracking the local map
+%
+%   This is an example helper function that is subject to change or removal 
+%   in future releases.
+%
+%   Inputs
+%   ------
+%   mapPoints         - A worldpointset object storing map points
+%   vSetKeyFrames     - An imageviewset storing key frames
+%   mapPointsIndices  - Indices of map points observed in the current frame
+%   featureIndices    - Indices of features in the current frame 
+%                       corresponding to map points denoted by mapPointsIndices                      
+%   currPose          - Current camera pose
+%   currFeatures      - ORB Features in the current frame 
+%   currPoints        - Feature points in the current frame
+%   intrinsics        - Camera intrinsics 
+%   scaleFactor       - scale factor of features
+%   numLevels         - number of levels in feature exatraction
+%   newKeyFrameAdded  - A boolean scalar indicating if a new key frame is
+%                       added recently
+%   lastKeyFrameIndex - Frame index of the last key frame
+%   currFrameIndex    - Frame index of the current frame
+%   numSkipFrames     - Largest number of frames to skip
+%   numPointsKeyFrame - Minimum number of points tracked by a key frame
+%   
+%   Outputs
+%   -------
+%   localKeyFrameIds  - ViewIds of the local key frames 
+%   currPose          - Refined camera pose of the current frame
+%   mapPointIdx       - Indices of map points observed in the current frame
+%   featureIdx        - Indices of features in the current frame corresponding
+%                       to mapPointIdx
+%   isKeyFrame        - A boolean scalar indicating if the current frame is
+%                       a key frame
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+persistent numPointsRefKeyFrame localPointsIndices localKeyFrameIdsInternal
+
+if isempty(numPointsRefKeyFrame) || newKeyFrameAdded
+    [localPointsIndices, localKeyFrameIdsInternal, numPointsRefKeyFrame] = ...
+    updateRefKeyFrameAndLocalPoints(mapPoints, vSetKeyFrames, mapPointIdx);
+end
+
+% Project the map into the frame and search for more map point correspondences
+newMapPointIdx = setdiff(localPointsIndices, mapPointIdx, 'stable');
+localFeatures  = getFeatures(mapPoints, vSetKeyFrames.Views, newMapPointIdx); 
+[projectedPoints, inlierIndex, predictedScales, viewAngles] = removeOutlierMapPoints(mapPoints, ...
+    currPose, intrinsics, newMapPointIdx, scaleFactor, numLevels);
+
+newMapPointIdx = newMapPointIdx(inlierIndex);
+localFeatures  = localFeatures(inlierIndex,:);
+
+unmatchedfeatureIdx = setdiff(cast((1:size( currFeatures.Features, 1)).', 'uint32'), ...
+    featureIdx,'stable');
+unmatchedFeatures   = currFeatures.Features(unmatchedfeatureIdx, :);
+unmatchedValidPoints= currPoints(unmatchedfeatureIdx);
+
+% Search radius depends on scale and view direction
+searchRadius    = 4*ones(size(localFeatures, 1), 1);
+searchRadius(viewAngles<3) = 2.5;
+searchRadius    = searchRadius.*predictedScales;
+
+indexPairs = matchFeaturesInRadius(binaryFeatures(localFeatures),...
+    binaryFeatures(unmatchedFeatures), unmatchedValidPoints, projectedPoints, ...
+    searchRadius, 'MatchThreshold', 40, 'MaxRatio', 0.9, 'Unique', true);
+
+% Filter by scales
+isGoodScale = currPoints.Scale(indexPairs(:, 2)) >= ...
+    max(1, predictedScales(indexPairs(:, 1))/scaleFactor) & ...
+    currPoints.Scale(indexPairs(:, 2)) <= predictedScales(indexPairs(:, 1));
+indexPairs  = indexPairs(isGoodScale, :);
+
+% Refine camera pose with more 3D-to-2D correspondences
+mapPointIdx   = [newMapPointIdx(indexPairs(:,1)); mapPointIdx];
+featureIdx     = [unmatchedfeatureIdx(indexPairs(:,2)); featureIdx];
+matchedMapPoints   = mapPoints.WorldPoints(mapPointIdx,:);
+matchedImagePoints = currPoints.Location(featureIdx,:);
+
+isKeyFrame = checkKeyFrame(numPointsRefKeyFrame, lastKeyFrameIndex, ...
+    currFrameIndex, mapPointIdx, numSkipFrames, numPointsKeyFrame);
+
+localKeyFrameIds = localKeyFrameIdsInternal;
+
+if isKeyFrame
+    % Refine camera pose only if the current frame is a key frame
+    currPose = bundleAdjustmentMotion(matchedMapPoints, matchedImagePoints, ...
+        currPose, intrinsics, 'PointsUndistorted', true, ...
+        'AbsoluteTolerance', 1e-7, 'RelativeTolerance', 1e-16,'MaxIteration', 20);
+end
+end
+
+function [localPointsIndices, localKeyFrameIds, numPointsRefKeyFrame] = ...
+    updateRefKeyFrameAndLocalPoints(mapPoints, vSetKeyFrames, pointIndices)
+
+if vSetKeyFrames.NumViews == 1
+    localKeyFrameIds = vSetKeyFrames.Views.ViewId;
+    localPointsIndices = (1:mapPoints.Count)';
+    numPointsRefKeyFrame = mapPoints.Count;
+    return
+end
+
+% The reference key frame has the most covisible map points 
+viewIds = findViewsOfWorldPoint(mapPoints, pointIndices);
+refKeyFrameId = mode(vertcat(viewIds{:}));
+
+localKeyFrames = connectedViews(vSetKeyFrames, refKeyFrameId, "MaxDistance", 2);
+localKeyFrameIds = [localKeyFrames.ViewId; refKeyFrameId];
+
+pointIdx = findWorldPointsInView(mapPoints, localKeyFrameIds);
+if iscell(pointIdx)
+    numPointsRefKeyFrame = numel(pointIdx{localKeyFrameIds==refKeyFrameId});
+    localPointsIndices = sort(vertcat(pointIdx{:}));
+else
+    numPointsRefKeyFrame = numel(pointIdx);
+    localPointsIndices = sort(pointIdx);
+end
+end
+
+function features = getFeatures(mapPoints, views, mapPointIdx)
+
+% Efficiently retrieve features and image points corresponding to map points
+% denoted by mapPointIdx
+allIndices = zeros(1, numel(mapPointIdx));
+
+% ViewId and offset pair
+count = []; % (ViewId, NumFeatures)
+viewsFeatures = views.Features;
+
+for i = 1:numel(mapPointIdx)
+    index3d  = mapPointIdx(i);
+    
+    viewId   = double(mapPoints.RepresentativeViewId(index3d));
+    
+    if isempty(count)
+        count = [viewId, size(viewsFeatures{viewId},1)];
+    elseif ~any(count(:,1) == viewId)
+        count = [count; viewId, size(viewsFeatures{viewId},1)];
+    end
+    
+    idx = find(count(:,1)==viewId);
+    
+    if idx > 1
+        offset = sum(count(1:idx-1,2));
+    else
+        offset = 0;
+    end
+    allIndices(i) = mapPoints.RepresentativeFeatureIndex(index3d) + offset;
+end
+
+uIds = count(:,1);
+
+% Concatenating features and indexing once is faster than accessing via a for loop
+allFeatures = vertcat(viewsFeatures{uIds});
+features    = allFeatures(allIndices, :);
+end
+
+function [projectedPoints, inliers, predictedScales, viewAngles] = removeOutlierMapPoints(...
+    mapPoints, pose, intrinsics, localPointsIndices, scaleFactor, ...
+    numLevels)
+
+% 1) Points within the image bounds
+xyzPoints = mapPoints.WorldPoints(localPointsIndices, :);
+[projectedPoints, isInImage] = world2img(xyzPoints, pose2extr(pose), intrinsics);
+
+if isempty(projectedPoints)
+    error('Tracking failed. Try inserting new key frames more frequently.')
+end
+
+% 2) Parallax less than 60 degrees
+cameraNormVector = [0 0 1] * pose.Rotation;
+cameraToPoints   = xyzPoints - pose.Translation;
+viewDirection    = mapPoints.ViewingDirection(localPointsIndices, :);
+validByView      = sum(viewDirection.*cameraToPoints, 2) > ...
+    cosd(60)*(vecnorm(cameraToPoints, 2, 2));
+
+% 3) Distance from map point to camera center is in the range of scale
+% invariant depth
+minDist          = mapPoints.DistanceLimits(localPointsIndices,1)/scaleFactor;
+maxDist          = mapPoints.DistanceLimits(localPointsIndices,2)*scaleFactor;
+dist             = vecnorm(xyzPoints - pose.Translation, 2, 2);
+
+validByDistance  = dist > minDist & dist < maxDist;
+
+inliers          = isInImage & validByView & validByDistance;
+
+% Predicted scales
+level= ceil(log(maxDist ./ dist)./log(scaleFactor));
+level(level<0)   = 0;
+level(level>=numLevels-1) = numLevels-1;
+predictedScales  = scaleFactor.^level;
+
+% View angles
+viewAngles       = acosd(sum(cameraNormVector.*cameraToPoints, 2) ./ ...
+    vecnorm(cameraToPoints, 2, 2));
+
+predictedScales  = predictedScales(inliers);
+viewAngles       = viewAngles(inliers);
+
+projectedPoints = projectedPoints(inliers, :);
+end
+
+function isKeyFrame = checkKeyFrame(numPointsRefKeyFrame, lastKeyFrameIndex, ...
+    currFrameIndex, mapPointsIndices, numSkipFrames, numPointsKeyFrame)
+
+% More than numSkipFrames frames have passed from last key frame insertion
+tooManyNonKeyFrames = currFrameIndex > lastKeyFrameIndex + numSkipFrames;
+
+% Track less than numPointsKeyFrame map points
+tooFewMapPoints     = numel(mapPointsIndices) < numPointsKeyFrame;
+
+% Tracked map points are fewer than 90% of points tracked by
+% the reference key frame
+tooFewTrackedPoints = numel(mapPointsIndices) < 0.9 * numPointsRefKeyFrame;
+
+isKeyFrame = (tooManyNonKeyFrames || tooFewMapPoints) && tooFewTrackedPoints;
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMatchedFeaturesRGBD.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMatchedFeaturesRGBD.m
new file mode 100644
index 0000000000000000000000000000000000000000..5aec70402a9a02803db91acb4e292a4e577e49cb
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMatchedFeaturesRGBD.m
@@ -0,0 +1,56 @@
+classdef helperVisualizeMatchedFeaturesRGBD < handle
+%helperVisualizeMatchedFeaturesRGBD show the matched features in a frame
+%
+%   This is an example helper class that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2021 The MathWorks, Inc.
+
+    properties (Access = private)
+        Image
+        
+        Feature
+    end
+    
+    methods (Access = public)
+        
+        function obj = helperVisualizeMatchedFeaturesRGBD(I1, I2, points)
+            
+            % Plot image
+            hFig  = figure;
+            hAxes = newplot(hFig); 
+            
+            % Set figure visibility and position
+            hFig.Visible = 'on';
+            movegui(hFig, [200 200]);
+            
+            % Show the image and features
+            obj.Image = showMatchedFeatures(I1, I2, points, ...
+                points, 'montage', 'Parent', hAxes, ...
+                'PlotOptions', {'g+','g+',''});
+            title(hAxes, 'Matched Features in Current Frame');
+            hold(hAxes, 'on');
+            
+            obj.Feature = findobj(hAxes.Parent,'Type','Line'); 
+        end 
+        
+        function updatePlot(obj, I1, I2, points)
+            
+            % Color and depth image
+            obj.Image.CData = imfuse(I1, I2, 'montage');
+            
+            % Connecting lines
+            obj.Feature(1).XData = NaN;
+            obj.Feature(1).YData = NaN;
+            
+            % Right image
+            obj.Feature(2).XData = points.Location(:,1) + size(I1, 2);
+            obj.Feature(2).YData = points.Location(:,2);
+            
+            % Left image
+            obj.Feature(3).XData = points.Location(:,1);
+            obj.Feature(3).YData = points.Location(:,2);
+            drawnow limitrate
+        end
+    end
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMotionAndStructure.m b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMotionAndStructure.m
new file mode 100644
index 0000000000000000000000000000000000000000..b064c0480c02a1f23f6c64ff7d6a4dfe3c723953
--- /dev/null
+++ b/target/classes/vslam/Mathworks_VSLAM_RGBD/helperVisualizeMotionAndStructure.m
@@ -0,0 +1,156 @@
+classdef helperVisualizeMotionAndStructure < handle
+%helperVisualizeMatchedFeatures show map points and camera trajectory
+%
+%   This is an example helper class that is subject to change or removal 
+%   in future releases.
+
+%   Copyright 2019-2022 The MathWorks, Inc.
+
+    properties
+        XLim = [-1.5 1.5]
+        
+        YLim = [-1 0.5]
+        
+        ZLim = [-0.5 2]
+        
+        Axes
+    end
+    
+    properties (Access = private)
+        MapPointsPlot
+ 
+        EstimatedTrajectory
+        
+        OptimizedTrajectory
+
+        CameraPlot
+    end
+
+    methods (Access = public)
+        function obj = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPoints, varargin)
+
+            if nargin > 2
+                obj.XLim = varargin{1};
+                obj.YLim = varargin{2};
+                obj.ZLim = varargin{3};
+            end
+        
+            [xyzPoints, currPose, trajectory]  = retrievePlottedData(obj, vSetKeyFrames, mapPoints);
+             
+            obj.MapPointsPlot = pcplayer(obj.XLim, obj.YLim, obj.ZLim, ...
+                'VerticalAxis', 'y', 'VerticalAxisDir', 'down');
+            
+            obj.Axes  = obj.MapPointsPlot.Axes;
+            obj.MapPointsPlot.view(xyzPoints); 
+            obj.Axes.Children.DisplayName = 'Map points';
+            
+            hold(obj.Axes, 'on');
+            
+            % Set figure position on the screen
+            movegui(obj.Axes.Parent, [1000 200]);
+            
+            % Plot camera trajectory
+            obj.EstimatedTrajectory = plot3(obj.Axes, trajectory(:,1), trajectory(:,2), ...
+                trajectory(:,3), 'r', 'LineWidth', 2 , 'DisplayName', 'Estimated trajectory');
+            
+            % Plot the current cameras
+            obj.CameraPlot = plotCamera(currPose, 'Parent', obj.Axes, 'Size', 0.05);
+        end
+        
+        function updatePlot(obj, vSetKeyFrames, mapPoints)
+            
+            [xyzPoints, currPose, trajectory]  = retrievePlottedData(obj, vSetKeyFrames, mapPoints);
+            
+            % Update the point cloud
+            obj.MapPointsPlot.view(xyzPoints);
+            
+            % Update the camera trajectory
+            set(obj.EstimatedTrajectory, 'XData', trajectory(:,1), 'YData', ...
+                trajectory(:,2), 'ZData', trajectory(:,3));
+            
+            % Update the current camera pose since the first camera is fixed
+            obj.CameraPlot.AbsolutePose = currPose.AbsolutePose;
+            obj.CameraPlot.Label        = num2str(currPose.ViewId);
+            
+            drawnow limitrate
+        end
+        
+        function plotOptimizedTrajectory(obj, poses)
+            
+            % Delete the camera plot
+            delete(obj.CameraPlot);
+            
+            % Plot the optimized trajectory
+            trans = vertcat(poses.AbsolutePose.Translation);
+            obj.OptimizedTrajectory = plot3(obj.Axes, trans(:, 1), trans(:, 2), trans(:, 3), 'm', ...
+                'LineWidth', 2, 'DisplayName', 'Optimized trajectory');
+        end
+        
+        function plotActualTrajectory(obj, gTruth, optimizedPoses)
+            estimatedCams = vertcat(optimizedPoses.AbsolutePose.Translation);
+            actualCams    = vertcat(gTruth.Translation);
+            scale = median(vecnorm(actualCams, 2, 2))/ median(vecnorm(estimatedCams, 2, 2));
+            
+            % Update the plot based on the ground truth
+            updatePlotScale(obj, scale);
+            
+            % Plot the ground truth
+            plot3(obj.Axes, actualCams(:,1), actualCams(:,2), actualCams(:,3), ...
+                'g','LineWidth',2, 'DisplayName', 'Actual trajectory');
+            
+            drawnow limitrate
+        end
+        
+        function showLegend(obj)
+            % Add a legend to the axes
+            hLegend = legend(obj.Axes, 'Location',  'northeast', ...
+                'TextColor', [1 1 1], 'FontWeight', 'bold');
+        end
+    end
+    
+    methods (Access = private)
+        function [xyzPoints, currPose, trajectory]  = retrievePlottedData(obj, vSetKeyFrames, mapPoints)
+            camPoses    = poses(vSetKeyFrames);
+            currPose    = camPoses(end,:); % Contains both ViewId and Pose
+
+            % Ensure the rotation matrix is a rigid transformation
+            R = double(currPose.AbsolutePose.R);
+            t = double(currPose.AbsolutePose.Translation);
+            [U, ~, V] = svd(R);
+            currPose.AbsolutePose.A = eye(4);
+            currPose.AbsolutePose.A(1:3, 4) = t;
+            currPose.AbsolutePose.A(1:3, 1:3) = U * V';
+
+            trajectory  = vertcat(camPoses.AbsolutePose.Translation);
+            xyzPoints   = mapPoints.WorldPoints;
+            
+            % Only plot the points within the limit
+            inPlotRange = xyzPoints(:, 1) > obj.XLim(1) & ...
+                xyzPoints(:, 1) < obj.XLim(2) & xyzPoints(:, 2) > obj.YLim(1) & ...
+                xyzPoints(:, 2) < obj.YLim(2) & xyzPoints(:, 3) > obj.ZLim(1) & ...
+                xyzPoints(:, 3) < obj.ZLim(2);
+            xyzPoints   = xyzPoints(inPlotRange, :);
+        end
+        
+        function updatePlotScale(obj, scale)
+            % Update the map points and camera trajectory based on the
+            % ground truth scale
+            obj.Axes.XLim = obj.Axes.XLim * scale;
+            obj.Axes.YLim = obj.Axes.YLim * scale;
+            obj.Axes.ZLim = obj.Axes.ZLim * scale;
+            
+            % Map points
+            obj.Axes.Children(end).XData = obj.Axes.Children(end).XData * scale;
+            obj.Axes.Children(end).YData = obj.Axes.Children(end).YData * scale;
+            obj.Axes.Children(end).ZData = obj.Axes.Children(end).ZData * scale;
+            
+            % Estiamted and optimized Camera trajectory
+            obj.EstimatedTrajectory.XData =  obj.EstimatedTrajectory.XData * scale;
+            obj.EstimatedTrajectory.YData =  obj.EstimatedTrajectory.YData * scale;
+            obj.EstimatedTrajectory.ZData =  obj.EstimatedTrajectory.ZData * scale;
+            obj.OptimizedTrajectory.XData =  obj.OptimizedTrajectory.XData * scale;
+            obj.OptimizedTrajectory.YData =  obj.OptimizedTrajectory.YData * scale;
+            obj.OptimizedTrajectory.ZData =  obj.OptimizedTrajectory.ZData * scale;
+        end
+    end
+end
\ No newline at end of file
diff --git a/target/classes/vslam/Mathworks_VSLAM_RGBD/orbslamGroundTruth.mat b/target/classes/vslam/Mathworks_VSLAM_RGBD/orbslamGroundTruth.mat
new file mode 100644
index 0000000000000000000000000000000000000000..ea1360e39c14cb70268bf6d6d4202b51eaf02014
Binary files /dev/null and b/target/classes/vslam/Mathworks_VSLAM_RGBD/orbslamGroundTruth.mat differ
diff --git a/target/classes/vslam/README 2.md b/target/classes/vslam/README 2.md
new file mode 100644
index 0000000000000000000000000000000000000000..3a958ebcebb9cd8a0278721e6c043284b4e5cad3
--- /dev/null
+++ b/target/classes/vslam/README 2.md	
@@ -0,0 +1,18 @@
+
+## Notes
+
+Notes from Rohan:
+- could use MATLAB coder to move MATLAB code to C/C++ code
+    - not sure if this is possible for Java code as well
+    - Prof. mentioned wanting Java code s.t. other students can read and critique codebase
+- use MATLAB functions, create new MATLAB objects for data structures / database system
+- dataset used by MATLAB example: https://cvg.cit.tum.de/data/datasets/rgbd-dataset 
+
+
+#### Performing VSLAM using online dataset 
+
+- Open up MATLAB console
+- Install necessary Mathworks Library: Vision, Visual SLAM (users will be queried to download necessary packages)
+- In MATLAB console, set imagesPath to 'rgbd_dataset_freiburg3_long_office_household/rgb'
+- Run the vslam_implementation.m script with the imagesPath as input
+- Use output of worldPointSet for figuring out which key features belong to which objects
diff --git a/target/classes/vslam/README.md b/target/classes/vslam/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3a958ebcebb9cd8a0278721e6c043284b4e5cad3
--- /dev/null
+++ b/target/classes/vslam/README.md
@@ -0,0 +1,18 @@
+
+## Notes
+
+Notes from Rohan:
+- could use MATLAB coder to move MATLAB code to C/C++ code
+    - not sure if this is possible for Java code as well
+    - Prof. mentioned wanting Java code s.t. other students can read and critique codebase
+- use MATLAB functions, create new MATLAB objects for data structures / database system
+- dataset used by MATLAB example: https://cvg.cit.tum.de/data/datasets/rgbd-dataset 
+
+
+#### Performing VSLAM using online dataset 
+
+- Open up MATLAB console
+- Install necessary Mathworks Library: Vision, Visual SLAM (users will be queried to download necessary packages)
+- In MATLAB console, set imagesPath to 'rgbd_dataset_freiburg3_long_office_household/rgb'
+- Run the vslam_implementation.m script with the imagesPath as input
+- Use output of worldPointSet for figuring out which key features belong to which objects
diff --git a/target/classes/vslam/extractPointsByViewId 2.m b/target/classes/vslam/extractPointsByViewId 2.m
new file mode 100644
index 0000000000000000000000000000000000000000..22dc739f5f31b73d47d098c401d0c5a38656e6a5
--- /dev/null
+++ b/target/classes/vslam/extractPointsByViewId 2.m	
@@ -0,0 +1,41 @@
+function extractPointsByViewId(viewId, worldPointSet)
+    % Define directories and file paths
+    keyFramesDir = './KeyFrames';
+    keyFramePointsDir = './KeyFramePoints';
+
+    % Construct filename for the image
+    imageFilename = sprintf('%s/KeyFrame_%04d.png', keyFramesDir, viewId);
+    
+    % Load and display the image
+    currImage = imread(imageFilename);
+    figure;
+    imshow(currImage);
+    title(['Image for View ID: ', num2str(viewId)]);
+    hold on;
+
+    % Load corresponding CSV file for world point indices and pixel locations
+    csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', keyFramePointsDir, viewId);
+    dataMatrix = readmatrix(csvFilename);
+
+    % Extract pixel locations and indices of world points
+    pixelLocations = dataMatrix(:, 1:2); % Assuming first two columns are pixel X, Y
+    mapPointsIdx = dataMatrix(:, 3);     % Assuming third column is mapPointsIdx
+
+    % Extract world points using the indices
+    worldPoints = worldPointSet.WorldPoints(mapPointsIdx, :);
+
+    % Append world points to the CSV
+    updatedDataMatrix = [dataMatrix, worldPoints]; % Concatenate world points
+    writematrix(updatedDataMatrix, csvFilename);   % Optionally write back if needed
+
+    % Overlay features on the image
+    plot(pixelLocations(:,1), pixelLocations(:,2), 'yo', 'MarkerSize', 5, 'LineWidth', 2);
+
+    % Optionally save or display the image
+    figure;
+    imshow(currImage);
+    hold on;
+    plot(pixelLocations(:,1), pixelLocations(:,2), 'yo', 'MarkerSize', 5, 'LineWidth', 2);
+    title('Features Overlayed on Image');
+end
+
diff --git a/target/classes/vslam/extractPointsByViewId.m b/target/classes/vslam/extractPointsByViewId.m
new file mode 100644
index 0000000000000000000000000000000000000000..22dc739f5f31b73d47d098c401d0c5a38656e6a5
--- /dev/null
+++ b/target/classes/vslam/extractPointsByViewId.m
@@ -0,0 +1,41 @@
+function extractPointsByViewId(viewId, worldPointSet)
+    % Define directories and file paths
+    keyFramesDir = './KeyFrames';
+    keyFramePointsDir = './KeyFramePoints';
+
+    % Construct filename for the image
+    imageFilename = sprintf('%s/KeyFrame_%04d.png', keyFramesDir, viewId);
+    
+    % Load and display the image
+    currImage = imread(imageFilename);
+    figure;
+    imshow(currImage);
+    title(['Image for View ID: ', num2str(viewId)]);
+    hold on;
+
+    % Load corresponding CSV file for world point indices and pixel locations
+    csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', keyFramePointsDir, viewId);
+    dataMatrix = readmatrix(csvFilename);
+
+    % Extract pixel locations and indices of world points
+    pixelLocations = dataMatrix(:, 1:2); % Assuming first two columns are pixel X, Y
+    mapPointsIdx = dataMatrix(:, 3);     % Assuming third column is mapPointsIdx
+
+    % Extract world points using the indices
+    worldPoints = worldPointSet.WorldPoints(mapPointsIdx, :);
+
+    % Append world points to the CSV
+    updatedDataMatrix = [dataMatrix, worldPoints]; % Concatenate world points
+    writematrix(updatedDataMatrix, csvFilename);   % Optionally write back if needed
+
+    % Overlay features on the image
+    plot(pixelLocations(:,1), pixelLocations(:,2), 'yo', 'MarkerSize', 5, 'LineWidth', 2);
+
+    % Optionally save or display the image
+    figure;
+    imshow(currImage);
+    hold on;
+    plot(pixelLocations(:,1), pixelLocations(:,2), 'yo', 'MarkerSize', 5, 'LineWidth', 2);
+    title('Features Overlayed on Image');
+end
+
diff --git a/target/classes/vslam/extractedPoints 2.csv b/target/classes/vslam/extractedPoints 2.csv
new file mode 100644
index 0000000000000000000000000000000000000000..482821170b96860c836ae47d6f7624d9469d8fb5
--- /dev/null
+++ b/target/classes/vslam/extractedPoints 2.csv	
@@ -0,0 +1,365 @@
+-0.06900241,-0.3507448,1.033868
+-0.5094872,-0.335972,1.037024
+-0.0517595,-0.3194826,0.964794
+-0.26819,-0.2832867,0.93624
+-0.451066,-0.2754324,0.9582117
+-0.02466401,-0.2934302,1.022113
+0.4340152,-0.2927349,1.012656
+-0.4700845,-0.2324494,1.027293
+0.05616835,-0.2302022,1.02122
+0.3103633,-0.2405539,1.076906
+0.3468663,-0.2287515,1.026217
+-0.2542701,-0.1819791,0.9472755
+0.2602769,-0.2096001,1.085634
+0.4181629,-0.1918874,1.018657
+0.5108834,-0.1945888,1.10052
+0.1607228,-0.1786381,1.092534
+0.1154751,-0.1575818,1.033309
+0.3628199,-0.1240209,1.042551
+0.3392987,-0.1220983,1.065156
+0.09428331,-0.09280027,1.005206
+-0.4141278,-0.08583868,1.030251
+0.18329,-0.09223963,0.997163
+0.1716043,-0.08562668,0.958635
+-0.1729519,-0.0776499,1.006449
+-0.2845822,-0.06999036,0.8611298
+0.02044802,-0.05811689,0.9738315
+0.01296036,-0.04444205,0.9208867
+-0.08239425,-0.03085459,0.9267675
+0.04727431,0.008490545,0.8688331
+-0.3606437,0.01618071,0.8629293
+0.2105094,0.1243638,0.933347
+0.231766,0.1069027,0.8321818
+-0.1770186,0.139959,0.7958759
+0.2364081,0.1642755,0.8707324
+0.2360844,0.3081827,0.8830881
+-0.4306689,-0.3407795,0.8945921
+-0.05465219,-0.3774999,0.96435
+-0.2250856,-0.3546759,0.9550002
+-0.246262,-0.3290255,0.9545395
+-0.2260483,-0.3236364,0.9466397
+-0.05509534,-0.3003376,0.9892556
+-0.4109164,-0.2374692,0.9288879
+-0.5153137,-0.2687777,1.098092
+-0.5362918,-0.2719595,1.141981
+0.05192059,-0.238798,0.9994154
+0.1607298,-0.2088129,1.080495
+0.09027376,-0.1664593,1.074121
+0.5117261,-0.152272,1.121635
+0.3421884,-0.1492289,1.072462
+-0.2698344,-0.07390544,0.8396418
+0.4053755,-0.07456393,0.9178874
+0.0910932,-0.0747536,0.914787
+0.1581096,-0.0611611,0.9377224
+-0.1005423,-0.06197135,0.9697764
+-0.1423956,-0.01718888,0.889078
+0.493636,0.2370742,0.998692
+-0.2270201,0.1787612,0.7168721
+-0.02916331,-0.338412,0.9608698
+-0.4426665,-0.2671321,0.982818
+0.2466568,-0.2226559,1.124538
+0.2462575,-0.2091596,1.095683
+0.1003007,-0.08707787,1.01655
+0.3871322,-0.08398501,0.9352465
+0.1269614,-0.06724115,0.9209728
+-0.2694361,-0.01734548,0.8628417
+-0.1826763,0.1571379,0.7704211
+0.09884058,0.231997,0.947727
+-0.3231615,0.2712583,0.827448
+-0.03420264,-0.3844759,0.9560074
+-0.2257674,-0.3436999,0.9292494
+-0.4242442,-0.3174223,0.8753457
+0.2805332,-0.1544295,1.103116
+0.1366949,-0.01871451,0.8879513
+0.4166071,-0.2877659,0.9980846
+0.3462467,-0.155378,1.067033
+-0.267102,-0.03911924,0.842447
+-0.1379147,0.2917985,0.8614042
+-0.06394307,-0.3850106,0.9949217
+0.2485076,-0.2154702,1.076664
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diff --git a/target/classes/vslam/extractedPoints.mat b/target/classes/vslam/extractedPoints.mat
new file mode 100644
index 0000000000000000000000000000000000000000..3c129dfb21ab775431bc17929e56a72434f926ce
Binary files /dev/null and b/target/classes/vslam/extractedPoints.mat differ
diff --git a/target/classes/vslam/optimizedPoses.mat b/target/classes/vslam/optimizedPoses.mat
new file mode 100644
index 0000000000000000000000000000000000000000..6530e386046ec69988fdea2577708629bed7c6c0
Binary files /dev/null and b/target/classes/vslam/optimizedPoses.mat differ
diff --git a/target/classes/vslam/pointCloudsAll.mat b/target/classes/vslam/pointCloudsAll.mat
new file mode 100644
index 0000000000000000000000000000000000000000..2dd6354ae44726ad71a8a2d85eea456fd8a3c93e
Binary files /dev/null and b/target/classes/vslam/pointCloudsAll.mat differ
diff --git a/target/classes/vslam/vslam_implementation 2.m b/target/classes/vslam/vslam_implementation 2.m
new file mode 100644
index 0000000000000000000000000000000000000000..dce4a7bb7faa29db097ce6fce0739b9c5269bf61
--- /dev/null
+++ b/target/classes/vslam/vslam_implementation 2.m	
@@ -0,0 +1,568 @@
+
+function worldPointSet = vslam_implementation(imagePath)
+    % Import dependencies
+    addpath('./Mathworks_VSLAM_Example/');
+
+    % Initialize image dataset
+    imds = imageDatastore(imagePath);
+
+    % Inspect the first image
+    currFrameIdx = 1;
+    currI = readimage(imds, currFrameIdx);
+    himage = imshow(currI);
+    
+    % Process the image sequence
+    worldPointSet = ProcessImageSequence(imds);
+
+
+end
+
+
+
+function worldPointSetOutput = ProcessImageSequence(imds)
+    currFrameIdx = 1;
+    currI = readimage(imds, currFrameIdx);
+
+    %% Map Initilization
+    % Set random seed for reproducibility
+    rng(0);
+    
+    % Create a cameraIntrinsics object to store the camera intrinsic parameters.
+    % The intrinsics for the dataset can be found at the following page:
+    % https://vision.in.tum.de/data/datasets/rgbd-dataset/file_formats
+    % Note that the images in the dataset are already undistorted, hence there
+    % is no need to specify the distortion coefficients.
+    focalLength    = [535.4, 539.2];    % in units of pixels
+    principalPoint = [320.1, 247.6];    % in units of pixels
+    imageSize      = size(currI,[1 2]);  % in units of pixels
+    intrinsics     = cameraIntrinsics(focalLength, principalPoint, imageSize);
+    
+    % Detect and extract ORB features
+    scaleFactor = 1.2;
+    numLevels   = 8;
+    numPoints   = 1000;
+    [preFeatures, prePoints] = helperDetectAndExtractFeatures(currI, scaleFactor, numLevels, numPoints); 
+    
+    currFrameIdx = currFrameIdx + 1;
+    firstI       = currI; % Preserve the first frame 
+    
+    isMapInitialized  = false;
+    
+    % Map initialization loop
+    while ~isMapInitialized && currFrameIdx < numel(imds.Files)
+        currI = readimage(imds, currFrameIdx);
+    
+        [currFeatures, currPoints] = helperDetectAndExtractFeatures(currI, scaleFactor, numLevels, numPoints); 
+    
+        currFrameIdx = currFrameIdx + 1;
+    
+        % Find putative feature matches
+        indexPairs = matchFeatures(preFeatures, currFeatures, Unique=true, ...
+            MaxRatio=0.9, MatchThreshold=40);
+    
+        preMatchedPoints  = prePoints(indexPairs(:,1),:);
+        currMatchedPoints = currPoints(indexPairs(:,2),:);
+    
+        % If not enough matches are found, check the next frame
+        minMatches = 100;
+        if size(indexPairs, 1) < minMatches
+            continue
+        end
+    
+        preMatchedPoints  = prePoints(indexPairs(:,1),:);
+        currMatchedPoints = currPoints(indexPairs(:,2),:);
+    
+        % Compute homography and evaluate reconstruction
+        [tformH, scoreH, inliersIdxH] = helperComputeHomography(preMatchedPoints, currMatchedPoints);
+    
+        % Compute fundamental matrix and evaluate reconstruction
+        [tformF, scoreF, inliersIdxF] = helperComputeFundamentalMatrix(preMatchedPoints, currMatchedPoints);
+    
+        % Select the model based on a heuristic
+        ratio = scoreH/(scoreH + scoreF);
+        ratioThreshold = 0.45;
+        if ratio > ratioThreshold
+            inlierTformIdx = inliersIdxH;
+            tform          = tformH;
+        else
+            inlierTformIdx = inliersIdxF;
+            tform          = tformF;
+        end
+    
+        % Computes the camera location up to scale. Use half of the 
+        % points to reduce computation
+        inlierPrePoints  = preMatchedPoints(inlierTformIdx);
+        inlierCurrPoints = currMatchedPoints(inlierTformIdx);
+        [relPose, validFraction] = estrelpose(tform, intrinsics, ...
+            inlierPrePoints(1:2:end), inlierCurrPoints(1:2:end));
+    
+        % If not enough inliers are found, move to the next frame
+        if validFraction < 0.9 || numel(relPose)==3
+            continue
+        end
+    
+        % Triangulate two views to obtain 3-D map points
+        minParallax = 1; % In degrees
+        [isValid, xyzWorldPoints, inlierTriangulationIdx] = helperTriangulateTwoFrames(...
+            rigidtform3d, relPose, inlierPrePoints, inlierCurrPoints, intrinsics, minParallax);
+    
+        if ~isValid
+            continue
+        end
+    
+        % Get the original index of features in the two key frames
+        indexPairs = indexPairs(inlierTformIdx(inlierTriangulationIdx),:);
+    
+        isMapInitialized = true;
+    
+        disp(['Map initialized with frame 1 and frame ', num2str(currFrameIdx-1)])
+    end % End of map initialization loop
+
+    %% Store initial key frames and map points
+    % Create an empty imageviewset object to store key frames
+    vSetKeyFrames = imageviewset;
+    
+    % Create an empty worldpointset object to store 3-D map points
+    mapPointSet   = worldpointset;
+    
+    % Add the first key frame. Place the camera associated with the first 
+    % key frame at the origin, oriented along the Z-axis
+    preViewId     = 1;
+    vSetKeyFrames = addView(vSetKeyFrames, preViewId, rigidtform3d, Points=prePoints,...
+        Features=preFeatures.Features);
+    
+    % Add the second key frame
+    currViewId    = 2;
+    vSetKeyFrames = addView(vSetKeyFrames, currViewId, relPose, Points=currPoints,...
+        Features=currFeatures.Features);
+    
+    % Add connection between the first and the second key frame
+    vSetKeyFrames = addConnection(vSetKeyFrames, preViewId, currViewId, relPose, Matches=indexPairs);
+    
+    % Add 3-D map points
+    [mapPointSet, newPointIdx] = addWorldPoints(mapPointSet, xyzWorldPoints);
+    
+    % Add observations of the map points
+    preLocations  = prePoints.Location;
+    currLocations = currPoints.Location;
+    preScales     = prePoints.Scale;
+    currScales    = currPoints.Scale;
+    
+    % Add image points corresponding to the map points in the first key frame
+    mapPointSet   = addCorrespondences(mapPointSet, preViewId, newPointIdx, indexPairs(:,1));
+    
+    % Add image points corresponding to the map points in the second key frame
+    mapPointSet   = addCorrespondences(mapPointSet, currViewId, newPointIdx, indexPairs(:,2));
+
+    % Initialize place recognition database
+    % Load the bag of features data created offline
+    bofData         = load("bagOfFeaturesDataSLAM.mat");
+    
+    % Initialize the place recognition database
+    loopDatabase    = invertedImageIndex(bofData.bof,SaveFeatureLocations=false);
+    
+    % Add features of the first two key frames to the database
+    addImageFeatures(loopDatabase, preFeatures, preViewId);
+    addImageFeatures(loopDatabase, currFeatures, currViewId);
+
+    %% Refine and visualize initial reconstruction
+    % Run full bundle adjustment on the first two key frames
+    tracks       = findTracks(vSetKeyFrames);
+    cameraPoses  = poses(vSetKeyFrames);
+    
+    [refinedPoints, refinedAbsPoses] = bundleAdjustment(xyzWorldPoints, tracks, ...
+        cameraPoses, intrinsics, FixedViewIDs=1, ...
+        PointsUndistorted=true, AbsoluteTolerance=1e-7,...
+        RelativeTolerance=1e-15, MaxIteration=20, ...
+        Solver="preconditioned-conjugate-gradient");
+
+    % Scale the map and the camera pose using the median depth of map points
+    medianDepth   = median(vecnorm(refinedPoints.'));
+    refinedPoints = refinedPoints / medianDepth;
+    
+    refinedAbsPoses.AbsolutePose(currViewId).Translation = ...
+        refinedAbsPoses.AbsolutePose(currViewId).Translation / medianDepth;
+    relPose.Translation = relPose.Translation/medianDepth;
+    
+    % Update key frames with the refined poses
+    vSetKeyFrames = updateView(vSetKeyFrames, refinedAbsPoses);
+    vSetKeyFrames = updateConnection(vSetKeyFrames, preViewId, currViewId, relPose);
+    
+    % Update map points with the refined positions
+    mapPointSet = updateWorldPoints(mapPointSet, newPointIdx, refinedPoints);
+    
+    % Update view direction and depth 
+    mapPointSet = updateLimitsAndDirection(mapPointSet, newPointIdx, vSetKeyFrames.Views);
+    
+    % Update representative view
+    mapPointSet = updateRepresentativeView(mapPointSet, newPointIdx, vSetKeyFrames.Views);
+    
+    % Visualize matched features in the current frame
+    % close(hfeature.Parent.Parent);
+    featurePlot   = helperVisualizeMatchedFeatures(currI, currPoints(indexPairs(:,2)));
+    
+    % Visualize initial map points and camera trajectory
+    mapPlot       = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPointSet);
+    
+    % Show legend
+    showLegend(mapPlot);
+
+    %% Tracking
+    % ViewId of the current key frame
+    currKeyFrameId   = currViewId;
+    
+    % ViewId of the last key frame
+    lastKeyFrameId   = currViewId;
+    
+    % Index of the last key frame in the input image sequence
+    lastKeyFrameIdx  = currFrameIdx - 1; 
+    
+    % Indices of all the key frames in the input image sequence
+    addedFramesIdx   = [1; lastKeyFrameIdx];
+    
+    isLoopClosed     = false;
+
+    % Main loop (attempt to close loop while iterating over all images in
+    % dataset)
+    isLastFrameKeyFrame = true;
+    while ~isLoopClosed && currFrameIdx < numel(imds.Files)  
+        currI = readimage(imds, currFrameIdx);
+    
+        [currFeatures, currPoints] = helperDetectAndExtractFeatures(currI, scaleFactor, numLevels, numPoints);
+    
+        % Track the last key frame
+        % mapPointsIdx:   Indices of the map points observed in the current frame
+        % featureIdx:     Indices of the corresponding feature points in the 
+        %                 current frame
+        [currPose, mapPointsIdx, featureIdx] = helperTrackLastKeyFrame(mapPointSet, ...
+            vSetKeyFrames.Views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor);
+    
+        % Track the local map and check if the current frame is a key frame.
+        % A frame is a key frame if both of the following conditions are satisfied:
+        %
+        % 1. At least 20 frames have passed since the last key frame or the
+        %    current frame tracks fewer than 100 map points.
+        % 2. The map points tracked by the current frame are fewer than 90% of
+        %    points tracked by the reference key frame.
+        %
+        % Tracking performance is sensitive to the value of numPointsKeyFrame.  
+        % If tracking is lost, try a larger value.
+        %
+        % localKeyFrameIds:   ViewId of the connected key frames of the current frame
+        numSkipFrames     = 20;
+        numPointsKeyFrame = 80;
+        [localKeyFrameIds, currPose, mapPointsIdx, featureIdx, isKeyFrame] = ...
+            helperTrackLocalMap(mapPointSet, vSetKeyFrames, mapPointsIdx, ...
+            featureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ...
+            isLastFrameKeyFrame, lastKeyFrameIdx, currFrameIdx, numSkipFrames, numPointsKeyFrame);
+
+    
+        % Visualize matched features
+        updatePlot(featurePlot, currI, currPoints(featureIdx));
+    
+        if ~isKeyFrame
+            currFrameIdx        = currFrameIdx + 1;
+            isLastFrameKeyFrame = false;
+            continue
+        else
+            isLastFrameKeyFrame = true;
+        end
+    
+        % Update current key frame ID
+        currKeyFrameId  = currKeyFrameId + 1;
+    
+        %% Local mapping
+        % Add the new key frame 
+        [mapPointSet, vSetKeyFrames] = helperAddNewKeyFrame(mapPointSet, vSetKeyFrames, ...
+            currPose, currFeatures, currPoints, mapPointsIdx, featureIdx, localKeyFrameIds);
+
+        % Remove outlier map points that are observed in fewer than 3 key frames
+        outlierIdx    = setdiff(newPointIdx, mapPointsIdx);
+        if ~isempty(outlierIdx)
+            mapPointSet   = removeWorldPoints(mapPointSet, outlierIdx);
+        end
+    
+        % Create new map points by triangulation
+        minNumMatches = 10;
+        minParallax   = 3;
+        [mapPointSet, vSetKeyFrames, newPointIdx] = helperCreateNewMapPoints(mapPointSet, vSetKeyFrames, ...
+            currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax);
+    
+        % Local bundle adjustment
+        [refinedViews, dist] = connectedViews(vSetKeyFrames, currKeyFrameId, MaxDistance=2);
+        refinedKeyFrameIds = refinedViews.ViewId;
+        fixedViewIds = refinedKeyFrameIds(dist==2);
+        fixedViewIds = fixedViewIds(1:min(10, numel(fixedViewIds)));
+    
+        % Refine local key frames and map points
+        [mapPointSet, vSetKeyFrames, mapPointIdx] = bundleAdjustment(...
+            mapPointSet, vSetKeyFrames, [refinedKeyFrameIds; currKeyFrameId], intrinsics, ...
+            FixedViewIDs=fixedViewIds, PointsUndistorted=true, AbsoluteTolerance=1e-7,...
+            RelativeTolerance=1e-16, Solver="preconditioned-conjugate-gradient", ...
+            MaxIteration=10);
+    
+        % Update view direction and depth
+        mapPointSet = updateLimitsAndDirection(mapPointSet, mapPointIdx, vSetKeyFrames.Views);
+    
+        % Update representative view
+        mapPointSet = updateRepresentativeView(mapPointSet, mapPointIdx, vSetKeyFrames.Views);
+    
+        % Check if the KeyFrames directory exists; if not, create it
+        keyFramesDir = './KeyFrames';
+        if ~exist(keyFramesDir, 'dir')
+            mkdir(keyFramesDir);
+        end
+
+        % Store feature locations for this key frame
+        keyFramePointsDir = './KeyFramePoints';
+        if ~exist(keyFramePointsDir, 'dir')
+            mkdir(keyFramePointsDir); 
+        end
+
+        % Save the current key frame image using currKeyFrameId
+        filename = sprintf('%s/KeyFrame_%04d.png', keyFramesDir, currKeyFrameId);
+        imwrite(currI, filename);
+
+        % Save feature points information
+        saveKeyFramePoints(keyFramePointsDir, currKeyFrameId, currPoints(featureIdx), mapPointsIdx);
+
+
+        % Visualize 3D world points and camera trajectory
+        updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
+
+        %% Loop closure
+        % Check loop closure after some key frames have been created    
+        if currKeyFrameId > 20
+    
+            % Minimum number of feature matches of loop edges
+            loopEdgeNumMatches = 50;
+    
+            % Detect possible loop closure key frame candidates
+            [isDetected, validLoopCandidates] = helperCheckLoopClosure(vSetKeyFrames, currKeyFrameId, ...
+                loopDatabase, currI, loopEdgeNumMatches);
+    
+            if isDetected 
+                % Add loop closure connections
+                [isLoopClosed, mapPointSet, vSetKeyFrames] = helperAddLoopConnections(...
+                    mapPointSet, vSetKeyFrames, validLoopCandidates, currKeyFrameId, ...
+                    currFeatures, loopEdgeNumMatches);
+            end
+        end
+    
+        % If no loop closure is detected, add current features into the database
+        if ~isLoopClosed
+            addImageFeatures(loopDatabase,  currFeatures, currKeyFrameId);
+        end
+    
+        % Update IDs and indices
+        lastKeyFrameId  = currKeyFrameId;
+        lastKeyFrameIdx = currFrameIdx;
+        addedFramesIdx  = [addedFramesIdx; currFrameIdx]; %#ok<AGROW>
+        currFrameIdx    = currFrameIdx + 1;
+    end % End of main loop
+
+    %% Optimizing
+    if isLoopClosed
+        % Optimize the poses
+        minNumMatches      = 20;
+        vSetKeyFramesOptim = optimizePoses(vSetKeyFrames, minNumMatches, Tolerance=1e-16);
+    
+        % Update map points after optimizing the poses
+        mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim);
+    
+        updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
+    
+        % Plot the optimized camera trajectory
+        optimizedPoses  = poses(vSetKeyFramesOptim);
+        plotOptimizedTrajectory(mapPlot, optimizedPoses)
+    
+        % Update legend
+        showLegend(mapPlot);
+    
+        worldPointSetOutput = mapPointSet;
+    end
+    
+end
+
+
+%% Helper functions
+% The following funciton definitions are provied in the
+% Mathworks_VSLAM_Example Directory
+% helperAddLoopConnections add connections between the current keyframe and the valid loop candidate.
+% helperAddNewKeyFrame add key frames to the key frame set.
+% helperCheckLoopClosure detect loop candidates key frames by retrieving visually similar images from the database.
+% helperCreateNewMapPoints create new map points by triangulation.
+% helperORBFeatureExtractorFunction implements the ORB feature extraction used in bagOfFeatures.
+% helperTrackLastKeyFrame estimate the current camera pose by tracking the last key frame.
+% helperTrackLocalMap refine the current camera pose by tracking the local map.
+% helperVisualizeMatchedFeatures show the matched features in a frame.
+% helperVisualizeMotionAndStructure show map points and camera trajectory.
+% helperImportGroundTruth import camera pose ground truth from the downloaded data.
+
+% helperDetectAndExtractFeatures detect and extract and ORB features from the image.
+function [features, validPoints] = helperDetectAndExtractFeatures(Irgb, ...
+    scaleFactor, numLevels, numPoints, varargin)
+
+    % In this example, the images are already undistorted. In a general
+    % workflow, uncomment the following code to undistort the images.
+    %
+    % if nargin > 4
+    %     intrinsics = varargin{1};
+    % end
+    % Irgb  = undistortImage(Irgb, intrinsics);
+    
+    % Detect ORB features
+    Igray  = im2gray(Irgb);
+    
+    points = detectORBFeatures(Igray, ScaleFactor=scaleFactor, NumLevels=numLevels);
+    
+    % Select a subset of features, uniformly distributed throughout the image
+    points = selectUniform(points, numPoints, size(Igray, 1:2));
+    
+    % Extract features
+    [features, validPoints] = extractFeatures(Igray, points);
+end
+
+% helperComputeHomography compute homography and evaluate reconstruction.
+function [H, score, inliersIndex] = helperComputeHomography(matchedPoints1, matchedPoints2)
+
+    [H, inliersLogicalIndex] = estgeotform2d( ...
+        matchedPoints1, matchedPoints2, "projective", ...
+        MaxNumTrials=1e3, MaxDistance=4, Confidence=90);
+    
+    inlierPoints1 = matchedPoints1(inliersLogicalIndex);
+    inlierPoints2 = matchedPoints2(inliersLogicalIndex);
+    
+    inliersIndex  = find(inliersLogicalIndex);
+    
+    locations1 = inlierPoints1.Location;
+    locations2 = inlierPoints2.Location;
+    xy1In2     = transformPointsForward(H, locations1);
+    xy2In1     = transformPointsInverse(H, locations2);
+    error1in2  = sum((locations2 - xy1In2).^2, 2);
+    error2in1  = sum((locations1 - xy2In1).^2, 2);
+    
+    outlierThreshold = 6;
+    
+    score = sum(max(outlierThreshold-error1in2, 0)) + ...
+        sum(max(outlierThreshold-error2in1, 0));
+end
+
+% helperComputeFundamentalMatrix compute fundamental matrix and evaluate reconstruction.
+function [F, score, inliersIndex] = helperComputeFundamentalMatrix(matchedPoints1, matchedPoints2)
+
+    [F, inliersLogicalIndex]   = estimateFundamentalMatrix( ...
+        matchedPoints1, matchedPoints2, Method="RANSAC",...
+        NumTrials=1e3, DistanceThreshold=4);
+    
+    inlierPoints1 = matchedPoints1(inliersLogicalIndex);
+    inlierPoints2 = matchedPoints2(inliersLogicalIndex);
+    
+    inliersIndex  = find(inliersLogicalIndex);
+    
+    locations1    = inlierPoints1.Location;
+    locations2    = inlierPoints2.Location;
+    
+    % Distance from points to epipolar line
+    lineIn1   = epipolarLine(F', locations2);
+    error2in1 = (sum([locations1, ones(size(locations1, 1),1)].* lineIn1, 2)).^2 ...
+        ./ sum(lineIn1(:,1:2).^2, 2);
+    lineIn2   = epipolarLine(F, locations1);
+    error1in2 = (sum([locations2, ones(size(locations2, 1),1)].* lineIn2, 2)).^2 ...
+        ./ sum(lineIn2(:,1:2).^2, 2);
+    
+    outlierThreshold = 4;
+    
+    score = sum(max(outlierThreshold-error1in2, 0)) + ...
+        sum(max(outlierThreshold-error2in1, 0));
+end
+
+% helperTriangulateTwoFrames triangulate two frames to initialize the map.
+function [isValid, xyzPoints, inlierIdx] = helperTriangulateTwoFrames(...
+    pose1, pose2, matchedPoints1, matchedPoints2, intrinsics, minParallax)
+
+    camMatrix1 = cameraProjection(intrinsics, pose2extr(pose1));
+    camMatrix2 = cameraProjection(intrinsics, pose2extr(pose2));
+    
+    [xyzPoints, reprojectionErrors, isInFront] = triangulate(matchedPoints1, ...
+        matchedPoints2, camMatrix1, camMatrix2);
+    
+    % Filter points by view direction and reprojection error
+    minReprojError = 1;
+    inlierIdx  = isInFront & reprojectionErrors < minReprojError;
+    xyzPoints  = xyzPoints(inlierIdx ,:);
+    
+    % A good two-view with significant parallax
+    ray1       = xyzPoints - pose1.Translation;
+    ray2       = xyzPoints - pose2.Translation;
+    cosAngle   = sum(ray1 .* ray2, 2) ./ (vecnorm(ray1, 2, 2) .* vecnorm(ray2, 2, 2));
+    
+    % Check parallax
+    isValid = all(cosAngle < cosd(minParallax) & cosAngle>0);
+end
+
+% helperEstimateTrajectoryError calculate the tracking error.
+function rmse = helperEstimateTrajectoryError(gTruth, cameraPoses)
+    locations       = vertcat(cameraPoses.AbsolutePose.Translation);
+    gLocations      = vertcat(gTruth.Translation);
+    scale           = median(vecnorm(gLocations, 2, 2))/ median(vecnorm(locations, 2, 2));
+    scaledLocations = locations * scale;
+    
+    rmse = sqrt(mean( sum((scaledLocations - gLocations).^2, 2) ));
+    disp(['Absolute RMSE for key frame trajectory (m): ', num2str(rmse)]);
+end
+
+% helperUpdateGlobalMap update 3-D locations of map points after pose graph optimization
+function mapPointSet = helperUpdateGlobalMap(...
+    mapPointSet, vSetKeyFrames, vSetKeyFramesOptim)
+    %helperUpdateGlobalMap update map points after pose graph optimization
+    posesOld     = vSetKeyFrames.Views.AbsolutePose;
+    posesNew     = vSetKeyFramesOptim.Views.AbsolutePose;
+    positionsOld = mapPointSet.WorldPoints;
+    positionsNew = positionsOld;
+    indices     = 1:mapPointSet.Count;
+    
+    % Update world location of each map point based on the new absolute pose of 
+    % the corresponding major view
+    for i = indices
+        majorViewIds = mapPointSet.RepresentativeViewId(i);
+        poseNew = posesNew(majorViewIds).A;
+        tform = affinetform3d(poseNew/posesOld(majorViewIds).A);
+        positionsNew(i, :) = transformPointsForward(tform, positionsOld(i, :));
+    end
+    mapPointSet = updateWorldPoints(mapPointSet, indices, positionsNew);
+end
+
+% function saveKeyFramePoints(dirPath, frameIndex, featurePoints)
+%     % Extract locations and corresponding point indices
+%     locations = featurePoints.Location;
+%     indices = (1:size(locations, 1))';  % Create an index array
+%     dataMatrix = [indices, locations];
+% 
+%     % Define filename for CSV
+%     csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', dirPath, frameIndex);
+% 
+%     % Write matrix to CSV
+%     writematrix(dataMatrix, csvFilename);
+% end
+
+function saveKeyFramePoints(dirPath, keyFrameId, featurePoints, mapPointsIdx)
+    % Ensure the directory exists
+    if ~exist(dirPath, 'dir')
+        mkdir(dirPath);
+    end
+
+    % Define the filename for the CSV file
+    csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', dirPath, keyFrameId);
+
+    % Extract pixel locations from the feature points
+    pixelLocations = featurePoints.Location;  % This should be an Nx2 matrix
+
+    % Combine the indices, pixel locations, and corresponding world points indices into one matrix
+    dataMatrix = [pixelLocations, mapPointsIdx];  % Concatenate horizontally
+
+    % Write the combined data to a CSV file
+    writematrix(dataMatrix, csvFilename);
+end
+
+
diff --git a/target/classes/vslam/vslam_implementation.m b/target/classes/vslam/vslam_implementation.m
new file mode 100644
index 0000000000000000000000000000000000000000..bfe1485ae3071229eee3b22daa230a5c6bfbce34
--- /dev/null
+++ b/target/classes/vslam/vslam_implementation.m
@@ -0,0 +1,568 @@
+
+function worldPointSet = vslam_implementation(imagePath)
+    % Import dependencies
+    addpath('./Mathworks_VSLAM_Example/');
+
+    % Initialize image dataset
+    imds = imageDatastore(imagePath);
+
+    % Inspect the first image
+    currFrameIdx = 1;
+    currI = readimage(imds, currFrameIdx);
+    himage = imshow(currI);
+    
+    % Process the image sequence
+    worldPointSet = ProcessImageSequence(imds);
+
+
+end
+
+
+
+function worldPointSetOutput = ProcessImageSequence(imds)
+    currFrameIdx = 1;
+    currI = readimage(imds, currFrameIdx);
+
+    %% Map Initilization
+    % Set random seed for reproducibility
+    rng(0);
+    
+    % Create a cameraIntrinsics object to store the camera intrinsic parameters.
+    % The intrinsics for the dataset can be found at the following page:
+    % https://vision.in.tum.de/data/datasets/rgbd-dataset/file_formats
+    % Note that the images in the dataset are already undistorted, hence there
+    % is no need to specify the distortion coefficients.
+    focalLength    = [535.4, 539.2];    % in units of pixels
+    principalPoint = [320.1, 247.6];    % in units of pixels
+    imageSize      = size(currI,[1 2]);  % in units of pixels
+    intrinsics     = cameraIntrinsics(focalLength, principalPoint, imageSize);
+    
+    % Detect and extract ORB features
+    scaleFactor = 1.2;
+    numLevels   = 8;
+    numPoints   = 1000;
+    [preFeatures, prePoints] = helperDetectAndExtractFeatures(currI, scaleFactor, numLevels, numPoints); 
+    
+    currFrameIdx = currFrameIdx + 1;
+    firstI       = currI; % Preserve the first frame 
+    
+    isMapInitialized  = false;
+    
+    % Map initialization loop
+    while ~isMapInitialized && currFrameIdx < numel(imds.Files)
+        currI = readimage(imds, currFrameIdx);
+    
+        [currFeatures, currPoints] = helperDetectAndExtractFeatures(currI, scaleFactor, numLevels, numPoints); 
+    
+        currFrameIdx = currFrameIdx + 1;
+    
+        % Find putative feature matches
+        indexPairs = matchFeatures(preFeatures, currFeatures, Unique=true, ...
+            MaxRatio=0.9, MatchThreshold=40);
+    
+        preMatchedPoints  = prePoints(indexPairs(:,1),:);
+        currMatchedPoints = currPoints(indexPairs(:,2),:);
+    
+        % If not enough matches are found, check the next frame
+        minMatches = 100;
+        if size(indexPairs, 1) < minMatches
+            continue
+        end
+    
+        preMatchedPoints  = prePoints(indexPairs(:,1),:);
+        currMatchedPoints = currPoints(indexPairs(:,2),:);
+    
+        % Compute homography and evaluate reconstruction
+        [tformH, scoreH, inliersIdxH] = helperComputeHomography(preMatchedPoints, currMatchedPoints);
+    
+        % Compute fundamental matrix and evaluate reconstruction
+        [tformF, scoreF, inliersIdxF] = helperComputeFundamentalMatrix(preMatchedPoints, currMatchedPoints);
+    
+        % Select the model based on a heuristic
+        ratio = scoreH/(scoreH + scoreF);
+        ratioThreshold = 0.45;
+        if ratio > ratioThreshold
+            inlierTformIdx = inliersIdxH;
+            tform          = tformH;
+        else
+            inlierTformIdx = inliersIdxF;
+            tform          = tformF;
+        end
+    
+        % Computes the camera location up to scale. Use half of the 
+        % points to reduce computation
+        inlierPrePoints  = preMatchedPoints(inlierTformIdx);
+        inlierCurrPoints = currMatchedPoints(inlierTformIdx);
+        [relPose, validFraction] = estrelpose(tform, intrinsics, ...
+            inlierPrePoints(1:2:end), inlierCurrPoints(1:2:end));
+    
+        % If not enough inliers are found, move to the next frame
+        if validFraction < 0.9 || numel(relPose)==3
+            continue
+        end
+    
+        % Triangulate two views to obtain 3-D map points
+        minParallax = 1; % In degrees
+        [isValid, xyzWorldPoints, inlierTriangulationIdx] = helperTriangulateTwoFrames(...
+            rigidtform3d, relPose, inlierPrePoints, inlierCurrPoints, intrinsics, minParallax);
+    
+        if ~isValid
+            continue
+        end
+    
+        % Get the original index of features in the two key frames
+        indexPairs = indexPairs(inlierTformIdx(inlierTriangulationIdx),:);
+    
+        isMapInitialized = true;
+    
+        disp(['Map initialized with frame 1 and frame ', num2str(currFrameIdx-1)])
+    end % End of map initialization loop
+
+    %% Store initial key frames and map points
+    % Create an empty imageviewset object to store key frames
+    vSetKeyFrames = imageviewset;
+    
+    % Create an empty worldpointset object to store 3-D map points
+    mapPointSet   = worldpointset;
+    
+    % Add the first key frame. Place the camera associated with the first 
+    % key frame at the origin, oriented along the Z-axis
+    preViewId     = 1;
+    vSetKeyFrames = addView(vSetKeyFrames, preViewId, rigidtform3d, Points=prePoints,...
+        Features=preFeatures.Features);
+    
+    % Add the second key frame
+    currViewId    = 2;
+    vSetKeyFrames = addView(vSetKeyFrames, currViewId, relPose, Points=currPoints,...
+        Features=currFeatures.Features);
+    
+    % Add connection between the first and the second key frame
+    vSetKeyFrames = addConnection(vSetKeyFrames, preViewId, currViewId, relPose, Matches=indexPairs);
+    
+    % Add 3-D map points
+    [mapPointSet, newPointIdx] = addWorldPoints(mapPointSet, xyzWorldPoints);
+    
+    % Add observations of the map points
+    preLocations  = prePoints.Location;
+    currLocations = currPoints.Location;
+    preScales     = prePoints.Scale;
+    currScales    = currPoints.Scale;
+    
+    % Add image points corresponding to the map points in the first key frame
+    mapPointSet   = addCorrespondences(mapPointSet, preViewId, newPointIdx, indexPairs(:,1));
+    
+    % Add image points corresponding to the map points in the second key frame
+    mapPointSet   = addCorrespondences(mapPointSet, currViewId, newPointIdx, indexPairs(:,2));
+
+    % Initialize place recognition database
+    % Load the bag of features data created offline
+    bofData         = load("bagOfFeaturesDataSLAM.mat");
+    
+    % Initialize the place recognition database
+    loopDatabase    = invertedImageIndex(bofData.bof,SaveFeatureLocations=false);
+    
+    % Add features of the first two key frames to the database
+    addImageFeatures(loopDatabase, preFeatures, preViewId);
+    addImageFeatures(loopDatabase, currFeatures, currViewId);
+
+    %% Refine and visualize initial reconstruction
+    % Run full bundle adjustment on the first two key frames
+    tracks       = findTracks(vSetKeyFrames);
+    cameraPoses  = poses(vSetKeyFrames);
+    
+    [refinedPoints, refinedAbsPoses] = bundleAdjustment(xyzWorldPoints, tracks, ...
+        cameraPoses, intrinsics, FixedViewIDs=1, ...
+        PointsUndistorted=true, AbsoluteTolerance=1e-7,...
+        RelativeTolerance=1e-15, MaxIteration=20, ...
+        Solver="preconditioned-conjugate-gradient");
+
+    % Scale the map and the camera pose using the median depth of map points
+    medianDepth   = median(vecnorm(refinedPoints.'));
+    refinedPoints = refinedPoints / medianDepth;
+    
+    refinedAbsPoses.AbsolutePose(currViewId).Translation = ...
+        refinedAbsPoses.AbsolutePose(currViewId).Translation / medianDepth;
+    relPose.Translation = relPose.Translation/medianDepth;
+    
+    % Update key frames with the refined poses
+    vSetKeyFrames = updateView(vSetKeyFrames, refinedAbsPoses);
+    vSetKeyFrames = updateConnection(vSetKeyFrames, preViewId, currViewId, relPose);
+    
+    % Update map points with the refined positions
+    mapPointSet = updateWorldPoints(mapPointSet, newPointIdx, refinedPoints);
+    
+    % Update view direction and depth 
+    mapPointSet = updateLimitsAndDirection(mapPointSet, newPointIdx, vSetKeyFrames.Views);
+    
+    % Update representative view
+    mapPointSet = updateRepresentativeView(mapPointSet, newPointIdx, vSetKeyFrames.Views);
+    
+    % Visualize matched features in the current frame
+    % close(hfeature.Parent.Parent);
+    featurePlot   = helperVisualizeMatchedFeatures(currI, currPoints(indexPairs(:,2)));
+    
+    % Visualize initial map points and camera trajectory
+    mapPlot       = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPointSet);
+    
+    % Show legend
+    showLegend(mapPlot);
+
+    %% Tracking
+    % ViewId of the current key frame
+    currKeyFrameId   = currViewId;
+    
+    % ViewId of the last key frame
+    lastKeyFrameId   = currViewId;
+    
+    % Index of the last key frame in the input image sequence
+    lastKeyFrameIdx  = currFrameIdx - 1; 
+    
+    % Indices of all the key frames in the input image sequence
+    addedFramesIdx   = [1; lastKeyFrameIdx];
+    
+    isLoopClosed     = false;
+
+    % Main loop (attempt to close loop while iterating over all images in
+    % dataset)
+    isLastFrameKeyFrame = true;
+    while ~isLoopClosed && currFrameIdx < numel(imds.Files)  
+        currI = readimage(imds, currFrameIdx);
+    
+        [currFeatures, currPoints] = helperDetectAndExtractFeatures(currI, scaleFactor, numLevels, numPoints);
+    
+        % Track the last key frame
+        % mapPointsIdx:   Indices of the map points observed in the current frame
+        % featureIdx:     Indices of the corresponding feature points in the 
+        %                 current frame
+        [currPose, mapPointsIdx, featureIdx] = helperTrackLastKeyFrame(mapPointSet, ...
+            vSetKeyFrames.Views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor);
+    
+        % Track the local map and check if the current frame is a key frame.
+        % A frame is a key frame if both of the following conditions are satisfied:
+        %
+        % 1. At least 20 frames have passed since the last key frame or the
+        %    current frame tracks fewer than 100 map points.
+        % 2. The map points tracked by the current frame are fewer than 90% of
+        %    points tracked by the reference key frame.
+        %
+        % Tracking performance is sensitive to the value of numPointsKeyFrame.  
+        % If tracking is lost, try a larger value.
+        %
+        % localKeyFrameIds:   ViewId of the connected key frames of the current frame
+        numSkipFrames     = 20;
+        numPointsKeyFrame = 80;
+        [localKeyFrameIds, currPose, mapPointsIdx, featureIdx, isKeyFrame] = ...
+            helperTrackLocalMap(mapPointSet, vSetKeyFrames, mapPointsIdx, ...
+            featureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ...
+            isLastFrameKeyFrame, lastKeyFrameIdx, currFrameIdx, numSkipFrames, numPointsKeyFrame);
+
+    
+        % Visualize matched features
+        updatePlot(featurePlot, currI, currPoints(featureIdx));
+    
+        if ~isKeyFrame
+            currFrameIdx        = currFrameIdx + 1;
+            isLastFrameKeyFrame = false;
+            continue
+        else
+            isLastFrameKeyFrame = true;
+        end
+    
+        % Update current key frame ID
+        currKeyFrameId  = currKeyFrameId + 1;
+    
+        %% Local mapping
+        % Add the new key frame 
+        [mapPointSet, vSetKeyFrames] = helperAddNewKeyFrame(mapPointSet, vSetKeyFrames, ...
+            currPose, currFeatures, currPoints, mapPointsIdx, featureIdx, localKeyFrameIds);
+
+        % Remove outlier map points that are observed in fewer than 3 key frames
+        outlierIdx    = setdiff(newPointIdx, mapPointsIdx);
+        if ~isempty(outlierIdx)
+            mapPointSet   = removeWorldPoints(mapPointSet, outlierIdx);
+        end
+    
+        % Create new map points by triangulation
+        minNumMatches = 10;
+        minParallax   = 3;
+        [mapPointSet, vSetKeyFrames, newPointIdx] = helperCreateNewMapPoints(mapPointSet, vSetKeyFrames, ...
+            currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax);
+    
+        % Local bundle adjustment
+        [refinedViews, dist] = connectedViews(vSetKeyFrames, currKeyFrameId, MaxDistance=2);
+        refinedKeyFrameIds = refinedViews.ViewId;
+        fixedViewIds = refinedKeyFrameIds(dist==2);
+        fixedViewIds = fixedViewIds(1:min(10, numel(fixedViewIds)));
+    
+        % Refine local key frames and map points
+        [mapPointSet, vSetKeyFrames, mapPointIdx] = bundleAdjustment(...
+            mapPointSet, vSetKeyFrames, [refinedKeyFrameIds; currKeyFrameId], intrinsics, ...
+            FixedViewIDs=fixedViewIds, PointsUndistorted=true, AbsoluteTolerance=1e-7,...
+            RelativeTolerance=1e-16, Solver="preconditioned-conjugate-gradient", ...
+            MaxIteration=10);
+    
+        % Update view direction and depth
+        mapPointSet = updateLimitsAndDirection(mapPointSet, mapPointIdx, vSetKeyFrames.Views);
+    
+        % Update representative view
+        mapPointSet = updateRepresentativeView(mapPointSet, mapPointIdx, vSetKeyFrames.Views);
+    
+        % Check if the KeyFrames directory exists; if not, create it
+        keyFramesDir = './KeyFrames_Mono';
+        if ~exist(keyFramesDir, 'dir')
+            mkdir(keyFramesDir);
+        end
+
+        % Store feature locations for this key frame
+        keyFramePointsDir = './KeyFramePoints_Mono';
+        if ~exist(keyFramePointsDir, 'dir')
+            mkdir(keyFramePointsDir); 
+        end
+
+        % Save the current key frame image using currKeyFrameId
+        filename = sprintf('%s/KeyFrame_%04d.png', keyFramesDir, currKeyFrameId);
+        imwrite(currI, filename);
+
+        % Save feature points information
+        saveKeyFramePoints(keyFramePointsDir, currKeyFrameId, currPoints(featureIdx), mapPointsIdx);
+
+
+        % Visualize 3D world points and camera trajectory
+        updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
+
+        %% Loop closure
+        % Check loop closure after some key frames have been created    
+        if currKeyFrameId > 20
+    
+            % Minimum number of feature matches of loop edges
+            loopEdgeNumMatches = 50;
+    
+            % Detect possible loop closure key frame candidates
+            [isDetected, validLoopCandidates] = helperCheckLoopClosure(vSetKeyFrames, currKeyFrameId, ...
+                loopDatabase, currI, loopEdgeNumMatches);
+    
+            if isDetected 
+                % Add loop closure connections
+                [isLoopClosed, mapPointSet, vSetKeyFrames] = helperAddLoopConnections(...
+                    mapPointSet, vSetKeyFrames, validLoopCandidates, currKeyFrameId, ...
+                    currFeatures, loopEdgeNumMatches);
+            end
+        end
+    
+        % If no loop closure is detected, add current features into the database
+        if ~isLoopClosed
+            addImageFeatures(loopDatabase,  currFeatures, currKeyFrameId);
+        end
+    
+        % Update IDs and indices
+        lastKeyFrameId  = currKeyFrameId;
+        lastKeyFrameIdx = currFrameIdx;
+        addedFramesIdx  = [addedFramesIdx; currFrameIdx]; %#ok<AGROW>
+        currFrameIdx    = currFrameIdx + 1;
+    end % End of main loop
+
+    %% Optimizing
+    if isLoopClosed
+        % Optimize the poses
+        minNumMatches      = 20;
+        vSetKeyFramesOptim = optimizePoses(vSetKeyFrames, minNumMatches, Tolerance=1e-16);
+    
+        % Update map points after optimizing the poses
+        mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim);
+    
+        updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
+    
+        % Plot the optimized camera trajectory
+        optimizedPoses  = poses(vSetKeyFramesOptim);
+        plotOptimizedTrajectory(mapPlot, optimizedPoses)
+    
+        % Update legend
+        showLegend(mapPlot);
+    
+        worldPointSetOutput = mapPointSet;
+    end
+    
+end
+
+
+%% Helper functions
+% The following funciton definitions are provied in the
+% Mathworks_VSLAM_Example Directory
+% helperAddLoopConnections add connections between the current keyframe and the valid loop candidate.
+% helperAddNewKeyFrame add key frames to the key frame set.
+% helperCheckLoopClosure detect loop candidates key frames by retrieving visually similar images from the database.
+% helperCreateNewMapPoints create new map points by triangulation.
+% helperORBFeatureExtractorFunction implements the ORB feature extraction used in bagOfFeatures.
+% helperTrackLastKeyFrame estimate the current camera pose by tracking the last key frame.
+% helperTrackLocalMap refine the current camera pose by tracking the local map.
+% helperVisualizeMatchedFeatures show the matched features in a frame.
+% helperVisualizeMotionAndStructure show map points and camera trajectory.
+% helperImportGroundTruth import camera pose ground truth from the downloaded data.
+
+% helperDetectAndExtractFeatures detect and extract and ORB features from the image.
+function [features, validPoints] = helperDetectAndExtractFeatures(Irgb, ...
+    scaleFactor, numLevels, numPoints, varargin)
+
+    % In this example, the images are already undistorted. In a general
+    % workflow, uncomment the following code to undistort the images.
+    %
+    % if nargin > 4
+    %     intrinsics = varargin{1};
+    % end
+    % Irgb  = undistortImage(Irgb, intrinsics);
+    
+    % Detect ORB features
+    Igray  = im2gray(Irgb);
+    
+    points = detectORBFeatures(Igray, ScaleFactor=scaleFactor, NumLevels=numLevels);
+    
+    % Select a subset of features, uniformly distributed throughout the image
+    points = selectUniform(points, numPoints, size(Igray, 1:2));
+    
+    % Extract features
+    [features, validPoints] = extractFeatures(Igray, points);
+end
+
+% helperComputeHomography compute homography and evaluate reconstruction.
+function [H, score, inliersIndex] = helperComputeHomography(matchedPoints1, matchedPoints2)
+
+    [H, inliersLogicalIndex] = estgeotform2d( ...
+        matchedPoints1, matchedPoints2, "projective", ...
+        MaxNumTrials=1e3, MaxDistance=4, Confidence=90);
+    
+    inlierPoints1 = matchedPoints1(inliersLogicalIndex);
+    inlierPoints2 = matchedPoints2(inliersLogicalIndex);
+    
+    inliersIndex  = find(inliersLogicalIndex);
+    
+    locations1 = inlierPoints1.Location;
+    locations2 = inlierPoints2.Location;
+    xy1In2     = transformPointsForward(H, locations1);
+    xy2In1     = transformPointsInverse(H, locations2);
+    error1in2  = sum((locations2 - xy1In2).^2, 2);
+    error2in1  = sum((locations1 - xy2In1).^2, 2);
+    
+    outlierThreshold = 6;
+    
+    score = sum(max(outlierThreshold-error1in2, 0)) + ...
+        sum(max(outlierThreshold-error2in1, 0));
+end
+
+% helperComputeFundamentalMatrix compute fundamental matrix and evaluate reconstruction.
+function [F, score, inliersIndex] = helperComputeFundamentalMatrix(matchedPoints1, matchedPoints2)
+
+    [F, inliersLogicalIndex]   = estimateFundamentalMatrix( ...
+        matchedPoints1, matchedPoints2, Method="RANSAC",...
+        NumTrials=1e3, DistanceThreshold=4);
+    
+    inlierPoints1 = matchedPoints1(inliersLogicalIndex);
+    inlierPoints2 = matchedPoints2(inliersLogicalIndex);
+    
+    inliersIndex  = find(inliersLogicalIndex);
+    
+    locations1    = inlierPoints1.Location;
+    locations2    = inlierPoints2.Location;
+    
+    % Distance from points to epipolar line
+    lineIn1   = epipolarLine(F', locations2);
+    error2in1 = (sum([locations1, ones(size(locations1, 1),1)].* lineIn1, 2)).^2 ...
+        ./ sum(lineIn1(:,1:2).^2, 2);
+    lineIn2   = epipolarLine(F, locations1);
+    error1in2 = (sum([locations2, ones(size(locations2, 1),1)].* lineIn2, 2)).^2 ...
+        ./ sum(lineIn2(:,1:2).^2, 2);
+    
+    outlierThreshold = 4;
+    
+    score = sum(max(outlierThreshold-error1in2, 0)) + ...
+        sum(max(outlierThreshold-error2in1, 0));
+end
+
+% helperTriangulateTwoFrames triangulate two frames to initialize the map.
+function [isValid, xyzPoints, inlierIdx] = helperTriangulateTwoFrames(...
+    pose1, pose2, matchedPoints1, matchedPoints2, intrinsics, minParallax)
+
+    camMatrix1 = cameraProjection(intrinsics, pose2extr(pose1));
+    camMatrix2 = cameraProjection(intrinsics, pose2extr(pose2));
+    
+    [xyzPoints, reprojectionErrors, isInFront] = triangulate(matchedPoints1, ...
+        matchedPoints2, camMatrix1, camMatrix2);
+    
+    % Filter points by view direction and reprojection error
+    minReprojError = 1;
+    inlierIdx  = isInFront & reprojectionErrors < minReprojError;
+    xyzPoints  = xyzPoints(inlierIdx ,:);
+    
+    % A good two-view with significant parallax
+    ray1       = xyzPoints - pose1.Translation;
+    ray2       = xyzPoints - pose2.Translation;
+    cosAngle   = sum(ray1 .* ray2, 2) ./ (vecnorm(ray1, 2, 2) .* vecnorm(ray2, 2, 2));
+    
+    % Check parallax
+    isValid = all(cosAngle < cosd(minParallax) & cosAngle>0);
+end
+
+% helperEstimateTrajectoryError calculate the tracking error.
+function rmse = helperEstimateTrajectoryError(gTruth, cameraPoses)
+    locations       = vertcat(cameraPoses.AbsolutePose.Translation);
+    gLocations      = vertcat(gTruth.Translation);
+    scale           = median(vecnorm(gLocations, 2, 2))/ median(vecnorm(locations, 2, 2));
+    scaledLocations = locations * scale;
+    
+    rmse = sqrt(mean( sum((scaledLocations - gLocations).^2, 2) ));
+    disp(['Absolute RMSE for key frame trajectory (m): ', num2str(rmse)]);
+end
+
+% helperUpdateGlobalMap update 3-D locations of map points after pose graph optimization
+function mapPointSet = helperUpdateGlobalMap(...
+    mapPointSet, vSetKeyFrames, vSetKeyFramesOptim)
+    %helperUpdateGlobalMap update map points after pose graph optimization
+    posesOld     = vSetKeyFrames.Views.AbsolutePose;
+    posesNew     = vSetKeyFramesOptim.Views.AbsolutePose;
+    positionsOld = mapPointSet.WorldPoints;
+    positionsNew = positionsOld;
+    indices     = 1:mapPointSet.Count;
+    
+    % Update world location of each map point based on the new absolute pose of 
+    % the corresponding major view
+    for i = indices
+        majorViewIds = mapPointSet.RepresentativeViewId(i);
+        poseNew = posesNew(majorViewIds).A;
+        tform = affinetform3d(poseNew/posesOld(majorViewIds).A);
+        positionsNew(i, :) = transformPointsForward(tform, positionsOld(i, :));
+    end
+    mapPointSet = updateWorldPoints(mapPointSet, indices, positionsNew);
+end
+
+% function saveKeyFramePoints(dirPath, frameIndex, featurePoints)
+%     % Extract locations and corresponding point indices
+%     locations = featurePoints.Location;
+%     indices = (1:size(locations, 1))';  % Create an index array
+%     dataMatrix = [indices, locations];
+% 
+%     % Define filename for CSV
+%     csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', dirPath, frameIndex);
+% 
+%     % Write matrix to CSV
+%     writematrix(dataMatrix, csvFilename);
+% end
+
+function saveKeyFramePoints(dirPath, keyFrameId, featurePoints, mapPointsIdx)
+    % Ensure the directory exists
+    if ~exist(dirPath, 'dir')
+        mkdir(dirPath);
+    end
+
+    % Define the filename for the CSV file
+    csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', dirPath, keyFrameId);
+
+    % Extract pixel locations from the feature points
+    pixelLocations = featurePoints.Location;  % This should be an Nx2 matrix
+
+    % Combine the indices, pixel locations, and corresponding world points indices into one matrix
+    dataMatrix = [pixelLocations, mapPointsIdx];  % Concatenate horizontally
+
+    % Write the combined data to a CSV file
+    writematrix(dataMatrix, csvFilename);
+end
+
+
diff --git a/target/classes/vslam/vslam_implementation_rgbd 2.asv b/target/classes/vslam/vslam_implementation_rgbd 2.asv
new file mode 100644
index 0000000000000000000000000000000000000000..875a7b2b4156ef690e3cd415ca2c176d3dc9e67e
--- /dev/null
+++ b/target/classes/vslam/vslam_implementation_rgbd 2.asv	
@@ -0,0 +1,181 @@
+function worldPointSet = vslam_implementation_rgbd(dataset_name)
+
+    baseFolder = './'
+    datasetFolder = [baseFolder, dataset_name, '/'];
+
+    if ~exist(datasetFolder, 'dir')
+        if(dataset_name == 'tum_rgbd_dataset')
+    
+            % Download if the dataset is not already downloaded
+    
+            
+            baseDownloadURL = "https://cvg.cit.tum.de/rgbd/dataset/freiburg3/rgbd_dataset_freiburg3_long_office_household.tgz"; 
+            dataFolder      = fullfile(tempdir, 'tum_rgbd_dataset', filesep); 
+            options         = weboptions('Timeout', Inf);
+            tgzFileName     = [dataFolder, 'fr3_office.tgz'];
+            folderExists    = exist(dataFolder, 'dir');
+            
+            % Create a folder in a temporary directory to save the downloaded file
+            if ~folderExists  
+                mkdir(dataFolder); 
+                disp('Downloading fr3_office.tgz (1.38 GB). This download can take a few minutes.') 
+                websave(tgzFileName, baseDownloadURL, options); 
+                
+                % Extract contents of the downloaded file
+                disp('Extracting fr3_office.tgz (1.38 GB) ...') 
+                untar(tgzFileName, dataFolder); 
+            end
+        
+            imageFolder = [dataFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        end
+    else
+        if (dataset_name == 'tum_rgbd_dataset')
+            imageFolder = [datasetFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        end
+    end
+
+
+
+    % Import dependencies
+    addpath('./Mathworks_VSLAM_RGBD/');
+
+    % Initialize image dataset
+    imgFolderColor = [imageFolder,'rgb/'];
+    imgFolderDepth = [imageFolder,'depth/'];
+    imdsColor      = imageDatastore(imgFolderColor);
+    imdsDepth      = imageDatastore(imgFolderDepth);
+    
+    
+    % Process the image sequence
+    worldPointSet = ProcessImageSequence(imdsColor, imdsDepth);
+end
+
+function worldPointSetOutput = ProcessImageSequence(imdsColor, imdsDepth)
+    
+    
+end
+
+%% Helper functions
+
+% helperImportTimestampFile Import time stamp file
+
+function timestamp = helperImportTimestampFile(filename)
+    % Input handling
+    dataLines = [4, Inf];
+    
+    %% Set up the Import Options and import the data
+    opts = delimitedTextImportOptions("NumVariables", 2);
+    
+    % Specify range and delimiter
+    opts.DataLines = dataLines;
+    opts.Delimiter = " ";
+    
+    % Specify column names and types
+    opts.VariableNames = ["VarName1", "Var2"];
+    opts.SelectedVariableNames = "VarName1";
+    opts.VariableTypes = ["double", "string"];
+    
+    % Specify file level properties
+    opts.ExtraColumnsRule = "ignore";
+    opts.EmptyLineRule = "read";
+    opts.ConsecutiveDelimitersRule = "join";
+    opts.LeadingDelimitersRule = "ignore";
+    
+    % Specify variable properties
+    opts = setvaropts(opts, "Var2", "WhitespaceRule", "preserve");
+    opts = setvaropts(opts, "Var2", "EmptyFieldRule", "auto");
+    
+    % Import the data
+    data = readtable(filename, opts);
+    
+    % Convert to output type
+    timestamp = table2array(data);
+end
+
+% helperAlignTimestamp align time stamp of color and depth images.
+function indexPairs = helperAlignTimestamp(timeColor, timeDepth)
+    idxDepth = 1;
+    indexPairs = zeros(numel(timeColor), 2);
+    for i = 1:numel(timeColor)
+        for j = idxDepth : numel(timeDepth)
+            if abs(timeColor(i) - timeDepth(j)) < 1e-4
+                idxDepth = j;
+                indexPairs(i, :) = [i, j];
+                break
+            elseif timeDepth(j) - timeColor(i) > 1e-3
+                break
+            end
+        end
+    end
+    indexPairs = indexPairs(indexPairs(:,1)>0, :);
+end
+
+% helperDetectAndExtractFeatures detect and extract and ORB features from the image.
+function [features, validPoints] = helperDetectAndExtractFeatures(Irgb, scaleFactor, numLevels)
+ 
+    numPoints = 1000;
+    
+    % Detect ORB features
+    Igray  = rgb2gray(Irgb);
+    
+    points = detectORBFeatures(Igray, ScaleFactor=scaleFactor, NumLevels=numLevels);
+    
+    % Select a subset of features, uniformly distributed throughout the image
+    points = selectUniform(points, numPoints, size(Igray, 1:2));
+    
+    % Extract features
+    [features, validPoints] = extractFeatures(Igray, points);
+end
+
+% helperReconstructFromRGBD reconstruct scene from color and depth image.
+
+function [xyzPoints, validIndex] = helperReconstructFromRGBD(points, ...
+    depthMap, intrinsics, currPose, depthFactor)
+
+    ptcloud = pcfromdepth(depthMap,depthFactor,intrinsics,ImagePoints=points, DepthRange=[0.1, 5]);
+    
+    isPointValid = ~isnan(ptcloud.Location(:, 1));
+    xyzPoints    = ptcloud.Location(isPointValid, :);
+    xyzPoints    = transformPointsForward(currPose, xyzPoints);
+    validIndex   = find(isPointValid);
+end
+
+% helperCullRecentMapPoints cull recently added map points.
+function [mapPointSet, mapPointsIdx] = ...
+    helperCullRecentMapPoints(mapPointSet, mapPointsIdx, newPointIdx, rgbdMapPointsIndices)
+    outlierIdx = setdiff([newPointIdx; rgbdMapPointsIndices], mapPointsIdx);
+    if ~isempty(outlierIdx)
+        mapPointSet   = removeWorldPoints(mapPointSet, outlierIdx);
+        mapPointsIdx  = mapPointsIdx - arrayfun(@(x) nnz(x>outlierIdx), mapPointsIdx);
+    end
+end
+
+% helperEstimateTrajectoryError calculate the tracking error.
+function rmse = helperEstimateTrajectoryError(gTruth, cameraPoses)
+    locations       = vertcat(cameraPoses.AbsolutePose.Translation);
+    gLocations      = vertcat(gTruth.Translation);
+    scale           = median(vecnorm(gLocations, 2, 2))/ median(vecnorm(locations, 2, 2));
+    scaledLocations = locations * scale;
+    
+    rmse = sqrt(mean( sum((scaledLocations - gLocations).^2, 2) ));
+    disp(['Absolute RMSE for key frame trajectory (m): ', num2str(rmse)]);
+end
+
+% helperUpdateGlobalMap update 3-D locations of map points after pose graph optimization
+function mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim)
+
+    posesOld     = vSetKeyFrames.Views.AbsolutePose;
+    posesNew     = vSetKeyFramesOptim.Views.AbsolutePose;
+    positionsOld = mapPointSet.WorldPoints;
+    positionsNew = positionsOld;
+    indices = 1:mapPointSet.Count;
+    
+    % Update world location of each map point based on the new absolute pose of 
+    % the corresponding major view
+    for i = 1: mapPointSet.Count
+        majorViewIds = mapPointSet.RepresentativeViewId(i);
+        tform = rigidtform3d(posesNew(majorViewIds).A/posesOld(majorViewIds).A);
+        positionsNew(i, :) = transformPointsForward(tform, positionsOld(i, :));
+    end
+    mapPointSet = updateWorldPoints(mapPointSet, indices, positionsNew);
+end
diff --git a/target/classes/vslam/vslam_implementation_rgbd 2.m b/target/classes/vslam/vslam_implementation_rgbd 2.m
new file mode 100644
index 0000000000000000000000000000000000000000..c63b2d8571746b2cd46b08329c01f175e2d52a77
--- /dev/null
+++ b/target/classes/vslam/vslam_implementation_rgbd 2.m	
@@ -0,0 +1,504 @@
+function worldPointSet = vslam_implementation_rgbd(dataset_name)
+    % Define the base folder for datasets
+    baseFolder = './';
+    datasetFolder = [baseFolder, dataset_name, '/'];
+
+    % Check if the dataset exists, if not download and prepare it
+    if ~exist(datasetFolder, 'dir')
+        if strcmp(dataset_name, 'tum_rgbd_dataset')
+            % Define the URL and local folder for download
+            baseDownloadURL = "https://cvg.cit.tum.de/rgbd/dataset/freiburg3/rgbd_dataset_freiburg3_long_office_household.tgz";
+            dataFolder = fullfile(baseFolder, 'tum_rgbd_dataset', filesep);
+            tgzFileName = [dataFolder, 'fr3_office.tgz'];
+
+            % Create a folder to save the downloaded file
+            if ~exist(dataFolder, 'dir')
+                mkdir(dataFolder);
+                disp('Downloading fr3_office.tgz (1.38 GB). This download can take a few minutes.');
+                h = waitbar(0, 'Downloading Dataset... Please wait.', 'Name', 'Downloading fr3_office');
+                websave(tgzFileName, baseDownloadURL, weboptions('Timeout', Inf));
+                % Update and close waitbar after download completes
+                waitbar(1, h, 'Download Complete. Extracting...');
+                pause(1); % Pause to show complete message
+                close(h);
+
+                % Extract contents of the downloaded file
+                disp('Extracting fr3_office.tgz (1.38 GB) ...');
+                h = waitbar(0, 'Extracting files... This may take a while.', 'Name', 'Extracting Data');
+                untar(tgzFileName, dataFolder);
+
+                % Close waitbar after extraction completes
+                waitbar(1, h, 'Extraction Complete.');
+                pause(1); % Pause to show complete message
+                close(h);
+            end
+
+            imageFolder = [dataFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        else
+            error('Dataset name not recognized or dataset-specific download steps not defined.');
+        end
+    else
+        % If dataset is already present, set the image folder path
+        if strcmp(dataset_name, 'tum_rgbd_dataset')
+            imageFolder = [datasetFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        end
+    end
+
+    % Import dependencies
+    addpath('./Mathworks_VSLAM_RGBD/');
+
+    % Initialize image dataset stores for color and depth images
+    imgFolderColor = [imageFolder, 'rgb/'];
+    imgFolderDepth = [imageFolder, 'depth/'];
+    imdsColor = imageDatastore(imgFolderColor);
+    imdsDepth = imageDatastore(imgFolderDepth);
+
+    % Note that the color and depth images are generated in an un-synchronized way in the dataset. Therefore, we need to associate color images to depth images based on the time stamp.
+    % Load time stamp data of color images
+    timeColor = helperImportTimestampFile([imageFolder, 'rgb.txt']);
+    
+    % Load time stamp data of depth images
+    timeDepth = helperImportTimestampFile([imageFolder, 'depth.txt']);
+    
+    % Align the time stamp
+    indexPairs = helperAlignTimestamp(timeColor, timeDepth);
+    
+    % Select the synchronized image data
+    imdsColor     = subset(imdsColor, indexPairs(:, 1));
+    imdsDepth     = subset(imdsDepth, indexPairs(:, 2));
+
+    % Process the image sequence
+    worldPointSet = ProcessImageSequence(imdsColor, imdsDepth);
+end
+
+
+function worldPointSetOutput = ProcessImageSequence(imdsColor, imdsDepth)
+    % Inspect the first RGB-D image
+    currFrameIdx  = 1;
+    currIcolor    = readimage(imdsColor, currFrameIdx);
+    currIdepth    = readimage(imdsDepth, currFrameIdx);
+    imshowpair(currIcolor, currIdepth, "montage");
+    
+    % Map Initialization: The pipeline starts by initializing the map that holds 3-D world points. 
+    % This step is crucial and has a significant impact on the accuracy of the final SLAM result. 
+    % Initial ORB feature points are extracted from the first color image using helperDetectAndExtractFeatures. 
+    % Their corresponding 3-D world locations can be computed from the pixel coordinates of the feature 
+    % points and the depth value using helperReconstructFromRGBD.
+
+    % Set random seed for reproducibility
+    rng(0);
+    
+    % Create a cameraIntrinsics object to store the camera intrinsic parameters.
+    % The intrinsics for the dataset can be found at the following page:
+    % https://vision.in.tum.de/data/datasets/rgbd-dataset/file_formats
+    focalLength    = [535.4, 539.2];    % in units of pixels
+    principalPoint = [320.1, 247.6];    % in units of pixels
+    imageSize      = size(currIcolor,[1,2]); % in pixels [mrows, ncols]
+    depthFactor    = 5e3;
+    intrinsics     = cameraIntrinsics(focalLength,principalPoint,imageSize);
+    
+    % Detect and extract ORB features from the color image
+    scaleFactor = 1.2;
+    numLevels   = 8;
+    [currFeatures, currPoints] = helperDetectAndExtractFeatures(currIcolor, scaleFactor, numLevels); 
+    
+    initialPose = rigidtform3d();
+    [xyzPoints, validIndex] = helperReconstructFromRGBD(currPoints, currIdepth, intrinsics, initialPose, depthFactor);
+
+    % Initialize Place Recognition Database
+    % Loop detection is performed using the bags-of-words approach. A visual vocabulary represented as a bagOfFeatures object is created offline with the ORB descriptors extracted from a large set of images in the dataset by calling:
+    % bag = bagOfFeatures(imds,CustomExtractor=@helperORBFeatureExtractorFunction, TreeProperties=[5, 10], StrongestFeatures=1);
+    % where imds is an imageDatastore object storing the training images and helperORBFeatureExtractorFunction is the ORB feature extractor function. See Image Retrieval with Bag of Visual Words for more information.
+    % The loop closure process incrementally builds a database, represented as an invertedImageIndex object, that stores the visual word-to-image mapping based on the bag of ORB features.
+
+    % Load the bag of features data created offline
+    bofData         = load("bagOfFeaturesDataSLAM.mat");
+    
+    % Initialize the place recognition database
+    loopDatabase    = invertedImageIndex(bofData.bof, SaveFeatureLocations=false);
+    
+    % Add features of the first key frame to the database
+    currKeyFrameId = 1;
+    addImageFeatures(loopDatabase, currFeatures, currKeyFrameId);
+
+    % Data Management and Visualization
+    % After the map is initialized using the first pair of color and depth image, you can use imageviewset and worldpointset to store the first key frames and the corresponding map points:
+
+    % Create an empty imageviewset object to store key frames
+    vSetKeyFrames = imageviewset;
+    
+    % Create an empty worldpointset object to store 3-D map points
+    mapPointSet   = worldpointset;
+    
+    % Add the first key frame
+    vSetKeyFrames = addView(vSetKeyFrames, currKeyFrameId, initialPose, Points=currPoints,...
+        Features=currFeatures.Features);
+    
+    % Add 3-D map points
+    [mapPointSet, rgbdMapPointsIdx] = addWorldPoints(mapPointSet, xyzPoints);
+    
+    % Add observations of the map points
+    mapPointSet = addCorrespondences(mapPointSet, currKeyFrameId, rgbdMapPointsIdx, validIndex);
+    
+    % Update view direction and depth
+    mapPointSet = updateLimitsAndDirection(mapPointSet, rgbdMapPointsIdx, vSetKeyFrames.Views);
+    
+    % Update representative view
+    mapPointSet = updateRepresentativeView(mapPointSet, rgbdMapPointsIdx, vSetKeyFrames.Views);
+    
+    % Visualize matched features in the first key frame
+    featurePlot = helperVisualizeMatchedFeaturesRGBD(currIcolor, currIdepth, currPoints(validIndex));
+    
+    % Visualize initial map points and camera trajectory
+    xLim = [-4 4];
+    yLim = [-3 1];
+    zLim = [-1 6];
+    mapPlot  = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPointSet, xLim, yLim, zLim);
+    
+    % Show legend
+    showLegend(mapPlot);
+
+    % Tracking
+    % The tracking process is performed using every RGB-D image and determines when to insert a new key frame. 
+    % ViewId of the last key frame
+    lastKeyFrameId    = currKeyFrameId;
+    
+    % Index of the last key frame in the input image sequence
+    lastKeyFrameIdx   = currFrameIdx; 
+    
+    % Indices of all the key frames in the input image sequence
+    addedFramesIdx    = lastKeyFrameIdx;
+    
+    currFrameIdx      = 2;
+    isLoopClosed      = false;
+
+    % Each frame is processed as follows:
+    % ORB features are extracted for each new color image and then matched (using matchFeatures), with features in the last key frame that have known corresponding 3-D map points.
+    % Estimate the camera pose using Perspective-n-Point algorithm, which estimates the pose of a calibrated camera given a set of 3-D points and their corresponding 2-D projections using estworldpose.
+    % Given the camera pose, project the map points observed by the last key frame into the current frame and search for feature correspondences using  matchFeaturesInRadius.
+    % With 3-D to 2-D correspondences in the current frame, refine the camera pose by performing a motion-only bundle adjustment using bundleAdjustmentMotion.
+    % Project the local map points into the current frame to search for more feature correspondences using matchFeaturesInRadius and refine the camera pose again using bundleAdjustmentMotion.
+    % The last step of tracking is to decide if the current frame should be a new key frame. A frame is a key frame if both of the following conditions are satisfied:
+    % At least 20 frames have passed since the last key frame or the current frame tracks fewer than 100 map points or 25% of points tracked by the reference key frame.
+    % The map points tracked by the current frame are fewer than 90% of points tracked by the reference key frame.
+    % If the current frame is to become a key frame, continue to the Local Mapping process. Otherwise, start Tracking for the next frame.
+    
+    % Main loop
+    isLastFrameKeyFrame = true;
+    while ~isLoopClosed && currFrameIdx < numel(imdsColor.Files)
+    
+        currIcolor = readimage(imdsColor, currFrameIdx);
+        currIdepth = readimage(imdsDepth, currFrameIdx);
+    
+        [currFeatures, currPoints]    = helperDetectAndExtractFeatures(currIcolor, scaleFactor, numLevels);
+    
+        % Track the last key frame
+        % trackedMapPointsIdx:  Indices of the map points observed in the current left frame 
+        % trackedFeatureIdx:    Indices of the corresponding feature points in the current left frame
+        [currPose, trackedMapPointsIdx, trackedFeatureIdx] = helperTrackLastKeyFrame(mapPointSet, ...
+            vSetKeyFrames.Views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor);
+        
+        if isempty(currPose) || numel(trackedMapPointsIdx) < 30
+            currFrameIdx = currFrameIdx + 1;
+            continue
+        end
+        
+        % Track the local map and check if the current frame is a key frame.
+        % A frame is a key frame if both of the following conditions are satisfied:
+        %
+        % 1. At least 20 frames have passed since the last key frame or the 
+        %    current frame tracks fewer than 100 map points. 
+        % 2. The map points tracked by the current frame are fewer than 90% of 
+        %    points tracked by the reference key frame.
+        %
+        % localKeyFrameIds:   ViewId of the connected key frames of the current frame
+        numSkipFrames     = 20;
+        numPointsKeyFrame = 100;
+        [localKeyFrameIds, currPose, trackedMapPointsIdx, trackedFeatureIdx, isKeyFrame] = ...
+            helperTrackLocalMap(mapPointSet, vSetKeyFrames, trackedMapPointsIdx, ...
+            trackedFeatureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ...
+            isLastFrameKeyFrame, lastKeyFrameIdx, currFrameIdx, numSkipFrames, numPointsKeyFrame);
+    
+        % Visualize matched features
+        updatePlot(featurePlot, currIcolor, currIdepth, currPoints(trackedFeatureIdx));
+        
+        if ~isKeyFrame
+            currFrameIdx = currFrameIdx + 1;
+            isLastFrameKeyFrame = false;
+            continue
+        else
+            % Match feature points between the stereo images and get the 3-D world positions
+            [xyzPoints, validIndex] = helperReconstructFromRGBD(currPoints, currIdepth, ...
+                intrinsics, currPose, depthFactor);
+    
+            [untrackedFeatureIdx, ia] = setdiff(validIndex, trackedFeatureIdx);
+            xyzPoints = xyzPoints(ia, :);
+            isLastFrameKeyFrame = true;
+        end
+    
+        % Update current key frame ID
+        currKeyFrameId  = currKeyFrameId + 1;
+
+        % Local Mapping
+        % Local mapping is performed for every key frame. When a new key frame is determined, add it to the key frames and update the attributes of the map points observed by the new key frame. To ensure that mapPointSet contains as few outliers as possible, a valid map point must be observed in at least 3 key frames. 
+        % New map points are created by triangulating ORB feature points in the current key frame and its connected key frames. For each unmatched feature point in the current key frame, search for a match with other unmatched points in the connected key frames using matchFeatures. The local bundle adjustment refines the pose of the current key frame, the poses of connected key frames, and all the map points observed in these key frames.
+
+        % Add the new key frame    
+        [mapPointSet, vSetKeyFrames] = helperAddNewKeyFrame(mapPointSet, vSetKeyFrames, ...
+            currPose, currFeatures, currPoints, trackedMapPointsIdx, trackedFeatureIdx, localKeyFrameIds);
+            
+        % Remove outlier map points that are observed in fewer than 3 key frames
+        if currKeyFrameId == 2
+            triangulatedMapPointsIdx = [];
+        end
+        
+        [mapPointSet, trackedMapPointsIdx] = ...
+            helperCullRecentMapPoints(mapPointSet, trackedMapPointsIdx, triangulatedMapPointsIdx, ...
+            rgbdMapPointsIdx);
+        
+        % Add new map points computed from disparity 
+        [mapPointSet, rgbdMapPointsIdx] = addWorldPoints(mapPointSet, xyzPoints);
+        mapPointSet = addCorrespondences(mapPointSet, currKeyFrameId, rgbdMapPointsIdx, ...
+            untrackedFeatureIdx);
+        
+        % Create new map points by triangulation
+        minNumMatches = 10;
+        minParallax   = 0.35;
+        [mapPointSet, vSetKeyFrames, triangulatedMapPointsIdx, rgbdMapPointsIdx] = helperCreateNewMapPointsStereo( ...
+            mapPointSet, vSetKeyFrames, currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax, ...
+            untrackedFeatureIdx, rgbdMapPointsIdx);
+    
+        % Update view direction and depth
+        mapPointSet = updateLimitsAndDirection(mapPointSet, [triangulatedMapPointsIdx; rgbdMapPointsIdx], ...
+            vSetKeyFrames.Views);
+    
+        % Update representative view
+        mapPointSet = updateRepresentativeView(mapPointSet, [triangulatedMapPointsIdx; rgbdMapPointsIdx], ...
+            vSetKeyFrames.Views);
+    
+        % Local bundle adjustment
+        [mapPointSet, vSetKeyFrames, triangulatedMapPointsIdx, rgbdMapPointsIdx] = ...
+            helperLocalBundleAdjustmentStereo(mapPointSet, vSetKeyFrames, ...
+            currKeyFrameId, intrinsics, triangulatedMapPointsIdx, rgbdMapPointsIdx);
+
+        % Check if the KeyFrames directory exists; if not, create it
+        keyFramesDir = './KeyFrames';
+        if ~exist(keyFramesDir, 'dir')
+            mkdir(keyFramesDir);
+        end
+
+        % Store feature locations for this key frame
+        keyFramePointsDir = './KeyFramePoints';
+        if ~exist(keyFramePointsDir, 'dir')
+            mkdir(keyFramePointsDir); 
+        end
+
+        % Save the current key frame image using currKeyFrameId
+        filename = sprintf('%s/KeyFrame_%04d.png', keyFramesDir, currKeyFrameId);
+        imwrite(currI, filename);
+
+        % Save feature points information
+        saveKeyFramePoints(keyFramePointsDir, currKeyFrameId, currPoints(trackedFeatureIdx), trackedMapPointsIdx);
+    
+        % Visualize 3-D world points and camera trajectory
+        updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
+
+        % Loop Closure
+        % The loop closure detection step takes the current key frame processed by the local mapping process and tries to detect and close the loop. Loop candidates are identified by querying images in the database that are visually similar to the current key frame using evaluateImageRetrieval. A candidate key frame is valid if it is not connected to the last key frame and three of its neighbor key frames are loop candidates.
+        % When a valid loop candidate is found, use estgeotform3d to compute the relative pose between the loop candidate frame and the current key frame. The relative pose represents a 3-D rigid transformation stored in a rigidtform3d object. Then add the loop connection with the relative pose and update mapPointSet and vSetKeyFrames.
+        % Check loop closure after some key frames have been created    
+        if currKeyFrameId > 20
+            
+            % Minimum number of feature matches of loop edges
+            loopEdgeNumMatches = 120;
+            
+            % Detect possible loop closure key frame candidates
+            [isDetected, validLoopCandidates] = helperCheckLoopClosure(vSetKeyFrames, currKeyFrameId, ...
+                loopDatabase, currIcolor, loopEdgeNumMatches);
+            
+            if isDetected 
+                % Add loop closure connections
+                maxDistance = 0.1;
+                [isLoopClosed, mapPointSet, vSetKeyFrames] = helperAddLoopConnectionsStereo(...
+                    mapPointSet, vSetKeyFrames, validLoopCandidates, currKeyFrameId, ...
+                    currFeatures, currPoints, loopEdgeNumMatches, maxDistance);
+            end
+        end
+        
+        % If no loop closure is detected, add current features into the database
+        if ~isLoopClosed
+            addImageFeatures(loopDatabase,  currFeatures, currKeyFrameId);
+        end
+        
+        % Update IDs and indices
+        lastKeyFrameId  = currKeyFrameId;
+        lastKeyFrameIdx = currFrameIdx;
+        addedFramesIdx  = [addedFramesIdx; currFrameIdx]; %#ok<AGROW>
+        currFrameIdx    = currFrameIdx + 1;
+    end % End of main loop
+
+    % Finally, apply pose graph optimization over the essential graph in vSetKeyFrames to correct the drift. The essential graph is created internally by removing connections with fewer than minNumMatches matches in the covisibility graph. After pose graph optimization, update the 3-D locations of the map points using the optimized poses.
+    
+    % Optimize the poses
+    minNumMatches      = 50;
+    vSetKeyFramesOptim = optimizePoses(vSetKeyFrames, minNumMatches, Tolerance=1e-16);
+    
+    % Update map points after optimizing the poses
+    mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim);
+    
+    updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
+    
+    % Plot the optimized camera trajectory
+    optimizedPoses  = poses(vSetKeyFramesOptim);
+    plotOptimizedTrajectory(mapPlot, optimizedPoses)
+    
+    % Update legend
+    showLegend(mapPlot);
+
+    worldPointSetOutput = mapPointSet;
+end
+
+%% Helper functions
+
+% helperImportTimestampFile Import time stamp file
+
+function timestamp = helperImportTimestampFile(filename)
+    % Input handling
+    dataLines = [4, Inf];
+    
+    %% Set up the Import Options and import the data
+    opts = delimitedTextImportOptions("NumVariables", 2);
+    
+    % Specify range and delimiter
+    opts.DataLines = dataLines;
+    opts.Delimiter = " ";
+    
+    % Specify column names and types
+    opts.VariableNames = ["VarName1", "Var2"];
+    opts.SelectedVariableNames = "VarName1";
+    opts.VariableTypes = ["double", "string"];
+    
+    % Specify file level properties
+    opts.ExtraColumnsRule = "ignore";
+    opts.EmptyLineRule = "read";
+    opts.ConsecutiveDelimitersRule = "join";
+    opts.LeadingDelimitersRule = "ignore";
+    
+    % Specify variable properties
+    opts = setvaropts(opts, "Var2", "WhitespaceRule", "preserve");
+    opts = setvaropts(opts, "Var2", "EmptyFieldRule", "auto");
+    
+    % Import the data
+    data = readtable(filename, opts);
+    
+    % Convert to output type
+    timestamp = table2array(data);
+end
+
+% helperAlignTimestamp align time stamp of color and depth images.
+function indexPairs = helperAlignTimestamp(timeColor, timeDepth)
+    idxDepth = 1;
+    indexPairs = zeros(numel(timeColor), 2);
+    for i = 1:numel(timeColor)
+        for j = idxDepth : numel(timeDepth)
+            if abs(timeColor(i) - timeDepth(j)) < 1e-4
+                idxDepth = j;
+                indexPairs(i, :) = [i, j];
+                break
+            elseif timeDepth(j) - timeColor(i) > 1e-3
+                break
+            end
+        end
+    end
+    indexPairs = indexPairs(indexPairs(:,1)>0, :);
+end
+
+% helperDetectAndExtractFeatures detect and extract and ORB features from the image.
+function [features, validPoints] = helperDetectAndExtractFeatures(Irgb, scaleFactor, numLevels)
+ 
+    numPoints = 1000;
+    
+    % Detect ORB features
+    Igray  = rgb2gray(Irgb);
+    
+    points = detectORBFeatures(Igray, ScaleFactor=scaleFactor, NumLevels=numLevels);
+    
+    % Select a subset of features, uniformly distributed throughout the image
+    points = selectUniform(points, numPoints, size(Igray, 1:2));
+    
+    % Extract features
+    [features, validPoints] = extractFeatures(Igray, points);
+end
+
+% helperReconstructFromRGBD reconstruct scene from color and depth image.
+
+function [xyzPoints, validIndex] = helperReconstructFromRGBD(points, ...
+    depthMap, intrinsics, currPose, depthFactor)
+
+    ptcloud = pcfromdepth(depthMap,depthFactor,intrinsics,ImagePoints=points, DepthRange=[0.1, 5]);
+    
+    isPointValid = ~isnan(ptcloud.Location(:, 1));
+    xyzPoints    = ptcloud.Location(isPointValid, :);
+    xyzPoints    = transformPointsForward(currPose, xyzPoints);
+    validIndex   = find(isPointValid);
+end
+
+% helperCullRecentMapPoints cull recently added map points.
+function [mapPointSet, mapPointsIdx] = ...
+    helperCullRecentMapPoints(mapPointSet, mapPointsIdx, newPointIdx, rgbdMapPointsIndices)
+    outlierIdx = setdiff([newPointIdx; rgbdMapPointsIndices], mapPointsIdx);
+    if ~isempty(outlierIdx)
+        mapPointSet   = removeWorldPoints(mapPointSet, outlierIdx);
+        mapPointsIdx  = mapPointsIdx - arrayfun(@(x) nnz(x>outlierIdx), mapPointsIdx);
+    end
+end
+
+% helperEstimateTrajectoryError calculate the tracking error.
+function rmse = helperEstimateTrajectoryError(gTruth, cameraPoses)
+    locations       = vertcat(cameraPoses.AbsolutePose.Translation);
+    gLocations      = vertcat(gTruth.Translation);
+    scale           = median(vecnorm(gLocations, 2, 2))/ median(vecnorm(locations, 2, 2));
+    scaledLocations = locations * scale;
+    
+    rmse = sqrt(mean( sum((scaledLocations - gLocations).^2, 2) ));
+    disp(['Absolute RMSE for key frame trajectory (m): ', num2str(rmse)]);
+end
+
+% helperUpdateGlobalMap update 3-D locations of map points after pose graph optimization
+function mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim)
+
+    posesOld     = vSetKeyFrames.Views.AbsolutePose;
+    posesNew     = vSetKeyFramesOptim.Views.AbsolutePose;
+    positionsOld = mapPointSet.WorldPoints;
+    positionsNew = positionsOld;
+    indices = 1:mapPointSet.Count;
+    
+    % Update world location of each map point based on the new absolute pose of 
+    % the corresponding major view
+    for i = 1: mapPointSet.Count
+        majorViewIds = mapPointSet.RepresentativeViewId(i);
+        tform = rigidtform3d(posesNew(majorViewIds).A/posesOld(majorViewIds).A);
+        positionsNew(i, :) = transformPointsForward(tform, positionsOld(i, :));
+    end
+    mapPointSet = updateWorldPoints(mapPointSet, indices, positionsNew);
+end
+
+% CSV file creation for points within keyframe
+function saveKeyFramePoints(dirPath, keyFrameId, featurePoints, mapPointsIdx)
+    % Ensure the directory exists
+    if ~exist(dirPath, 'dir')
+        mkdir(dirPath);
+    end
+
+    % Define the filename for the CSV file
+    csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', dirPath, keyFrameId);
+
+    % Extract pixel locations from the feature points
+    pixelLocations = featurePoints.Location;  % This should be an Nx2 matrix
+
+    % Combine the indices, pixel locations, and corresponding world points indices into one matrix
+    dataMatrix = [pixelLocations, mapPointsIdx];  % Concatenate horizontally
+
+    % Write the combined data to a CSV file
+    writematrix(dataMatrix, csvFilename);
+end
diff --git a/target/classes/vslam/vslam_implementation_rgbd.asv b/target/classes/vslam/vslam_implementation_rgbd.asv
new file mode 100644
index 0000000000000000000000000000000000000000..875a7b2b4156ef690e3cd415ca2c176d3dc9e67e
--- /dev/null
+++ b/target/classes/vslam/vslam_implementation_rgbd.asv
@@ -0,0 +1,181 @@
+function worldPointSet = vslam_implementation_rgbd(dataset_name)
+
+    baseFolder = './'
+    datasetFolder = [baseFolder, dataset_name, '/'];
+
+    if ~exist(datasetFolder, 'dir')
+        if(dataset_name == 'tum_rgbd_dataset')
+    
+            % Download if the dataset is not already downloaded
+    
+            
+            baseDownloadURL = "https://cvg.cit.tum.de/rgbd/dataset/freiburg3/rgbd_dataset_freiburg3_long_office_household.tgz"; 
+            dataFolder      = fullfile(tempdir, 'tum_rgbd_dataset', filesep); 
+            options         = weboptions('Timeout', Inf);
+            tgzFileName     = [dataFolder, 'fr3_office.tgz'];
+            folderExists    = exist(dataFolder, 'dir');
+            
+            % Create a folder in a temporary directory to save the downloaded file
+            if ~folderExists  
+                mkdir(dataFolder); 
+                disp('Downloading fr3_office.tgz (1.38 GB). This download can take a few minutes.') 
+                websave(tgzFileName, baseDownloadURL, options); 
+                
+                % Extract contents of the downloaded file
+                disp('Extracting fr3_office.tgz (1.38 GB) ...') 
+                untar(tgzFileName, dataFolder); 
+            end
+        
+            imageFolder = [dataFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        end
+    else
+        if (dataset_name == 'tum_rgbd_dataset')
+            imageFolder = [datasetFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        end
+    end
+
+
+
+    % Import dependencies
+    addpath('./Mathworks_VSLAM_RGBD/');
+
+    % Initialize image dataset
+    imgFolderColor = [imageFolder,'rgb/'];
+    imgFolderDepth = [imageFolder,'depth/'];
+    imdsColor      = imageDatastore(imgFolderColor);
+    imdsDepth      = imageDatastore(imgFolderDepth);
+    
+    
+    % Process the image sequence
+    worldPointSet = ProcessImageSequence(imdsColor, imdsDepth);
+end
+
+function worldPointSetOutput = ProcessImageSequence(imdsColor, imdsDepth)
+    
+    
+end
+
+%% Helper functions
+
+% helperImportTimestampFile Import time stamp file
+
+function timestamp = helperImportTimestampFile(filename)
+    % Input handling
+    dataLines = [4, Inf];
+    
+    %% Set up the Import Options and import the data
+    opts = delimitedTextImportOptions("NumVariables", 2);
+    
+    % Specify range and delimiter
+    opts.DataLines = dataLines;
+    opts.Delimiter = " ";
+    
+    % Specify column names and types
+    opts.VariableNames = ["VarName1", "Var2"];
+    opts.SelectedVariableNames = "VarName1";
+    opts.VariableTypes = ["double", "string"];
+    
+    % Specify file level properties
+    opts.ExtraColumnsRule = "ignore";
+    opts.EmptyLineRule = "read";
+    opts.ConsecutiveDelimitersRule = "join";
+    opts.LeadingDelimitersRule = "ignore";
+    
+    % Specify variable properties
+    opts = setvaropts(opts, "Var2", "WhitespaceRule", "preserve");
+    opts = setvaropts(opts, "Var2", "EmptyFieldRule", "auto");
+    
+    % Import the data
+    data = readtable(filename, opts);
+    
+    % Convert to output type
+    timestamp = table2array(data);
+end
+
+% helperAlignTimestamp align time stamp of color and depth images.
+function indexPairs = helperAlignTimestamp(timeColor, timeDepth)
+    idxDepth = 1;
+    indexPairs = zeros(numel(timeColor), 2);
+    for i = 1:numel(timeColor)
+        for j = idxDepth : numel(timeDepth)
+            if abs(timeColor(i) - timeDepth(j)) < 1e-4
+                idxDepth = j;
+                indexPairs(i, :) = [i, j];
+                break
+            elseif timeDepth(j) - timeColor(i) > 1e-3
+                break
+            end
+        end
+    end
+    indexPairs = indexPairs(indexPairs(:,1)>0, :);
+end
+
+% helperDetectAndExtractFeatures detect and extract and ORB features from the image.
+function [features, validPoints] = helperDetectAndExtractFeatures(Irgb, scaleFactor, numLevels)
+ 
+    numPoints = 1000;
+    
+    % Detect ORB features
+    Igray  = rgb2gray(Irgb);
+    
+    points = detectORBFeatures(Igray, ScaleFactor=scaleFactor, NumLevels=numLevels);
+    
+    % Select a subset of features, uniformly distributed throughout the image
+    points = selectUniform(points, numPoints, size(Igray, 1:2));
+    
+    % Extract features
+    [features, validPoints] = extractFeatures(Igray, points);
+end
+
+% helperReconstructFromRGBD reconstruct scene from color and depth image.
+
+function [xyzPoints, validIndex] = helperReconstructFromRGBD(points, ...
+    depthMap, intrinsics, currPose, depthFactor)
+
+    ptcloud = pcfromdepth(depthMap,depthFactor,intrinsics,ImagePoints=points, DepthRange=[0.1, 5]);
+    
+    isPointValid = ~isnan(ptcloud.Location(:, 1));
+    xyzPoints    = ptcloud.Location(isPointValid, :);
+    xyzPoints    = transformPointsForward(currPose, xyzPoints);
+    validIndex   = find(isPointValid);
+end
+
+% helperCullRecentMapPoints cull recently added map points.
+function [mapPointSet, mapPointsIdx] = ...
+    helperCullRecentMapPoints(mapPointSet, mapPointsIdx, newPointIdx, rgbdMapPointsIndices)
+    outlierIdx = setdiff([newPointIdx; rgbdMapPointsIndices], mapPointsIdx);
+    if ~isempty(outlierIdx)
+        mapPointSet   = removeWorldPoints(mapPointSet, outlierIdx);
+        mapPointsIdx  = mapPointsIdx - arrayfun(@(x) nnz(x>outlierIdx), mapPointsIdx);
+    end
+end
+
+% helperEstimateTrajectoryError calculate the tracking error.
+function rmse = helperEstimateTrajectoryError(gTruth, cameraPoses)
+    locations       = vertcat(cameraPoses.AbsolutePose.Translation);
+    gLocations      = vertcat(gTruth.Translation);
+    scale           = median(vecnorm(gLocations, 2, 2))/ median(vecnorm(locations, 2, 2));
+    scaledLocations = locations * scale;
+    
+    rmse = sqrt(mean( sum((scaledLocations - gLocations).^2, 2) ));
+    disp(['Absolute RMSE for key frame trajectory (m): ', num2str(rmse)]);
+end
+
+% helperUpdateGlobalMap update 3-D locations of map points after pose graph optimization
+function mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim)
+
+    posesOld     = vSetKeyFrames.Views.AbsolutePose;
+    posesNew     = vSetKeyFramesOptim.Views.AbsolutePose;
+    positionsOld = mapPointSet.WorldPoints;
+    positionsNew = positionsOld;
+    indices = 1:mapPointSet.Count;
+    
+    % Update world location of each map point based on the new absolute pose of 
+    % the corresponding major view
+    for i = 1: mapPointSet.Count
+        majorViewIds = mapPointSet.RepresentativeViewId(i);
+        tform = rigidtform3d(posesNew(majorViewIds).A/posesOld(majorViewIds).A);
+        positionsNew(i, :) = transformPointsForward(tform, positionsOld(i, :));
+    end
+    mapPointSet = updateWorldPoints(mapPointSet, indices, positionsNew);
+end
diff --git a/target/classes/vslam/vslam_implementation_rgbd.m b/target/classes/vslam/vslam_implementation_rgbd.m
new file mode 100644
index 0000000000000000000000000000000000000000..ad7cd6a06ec6f0126c036618b17892b74f14901d
--- /dev/null
+++ b/target/classes/vslam/vslam_implementation_rgbd.m
@@ -0,0 +1,544 @@
+function [worldPointSetOutput, optimizedPoses, pointCloudsAll] = vslam_implementation_rgbd(dataset_name)
+    % Define the base folder for datasets
+    baseFolder = './';
+    datasetFolder = [baseFolder, dataset_name, '/'];
+
+    % Check if the dataset exists, if not download and prepare it
+    if ~exist(datasetFolder, 'dir')
+        if strcmp(dataset_name, 'tum_rgbd_dataset')
+            % Define the URL and local folder for download
+            baseDownloadURL = "https://cvg.cit.tum.de/rgbd/dataset/freiburg3/rgbd_dataset_freiburg3_long_office_household.tgz";
+            dataFolder = fullfile(baseFolder, 'tum_rgbd_dataset', filesep);
+            tgzFileName = [dataFolder, 'fr3_office.tgz'];
+
+            % Create a folder to save the downloaded file
+            if ~exist(dataFolder, 'dir')
+                mkdir(dataFolder);
+                disp('Downloading fr3_office.tgz (1.38 GB). This download can take a few minutes.');
+                h = waitbar(0, 'Downloading Dataset... Please wait.', 'Name', 'Downloading fr3_office');
+                websave(tgzFileName, baseDownloadURL, weboptions('Timeout', Inf));
+                % Update and close waitbar after download completes
+                waitbar(1, h, 'Download Complete. Extracting...');
+                pause(1); % Pause to show complete message
+                close(h);
+
+                % Extract contents of the downloaded file
+                disp('Extracting fr3_office.tgz (1.38 GB) ...');
+                h = waitbar(0, 'Extracting files... This may take a while.', 'Name', 'Extracting Data');
+                untar(tgzFileName, dataFolder);
+
+                % Close waitbar after extraction completes
+                waitbar(1, h, 'Extraction Complete.');
+                pause(1); % Pause to show complete message
+                close(h);
+            end
+
+            imageFolder = [dataFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        else
+            error('Dataset name not recognized or dataset-specific download steps not defined.');
+        end
+    else
+        % If dataset is already present, set the image folder path
+        if strcmp(dataset_name, 'tum_rgbd_dataset')
+            imageFolder = [datasetFolder, 'rgbd_dataset_freiburg3_long_office_household/'];
+        end
+    end
+
+    % Import dependencies
+    addpath('./Mathworks_VSLAM_RGBD/');
+
+    % Initialize image dataset stores for color and depth images
+    imgFolderColor = [imageFolder, 'rgb/'];
+    imgFolderDepth = [imageFolder, 'depth/'];
+    imdsColor = imageDatastore(imgFolderColor);
+    imdsDepth = imageDatastore(imgFolderDepth);
+
+    % Note that the color and depth images are generated in an un-synchronized way in the dataset. Therefore, we need to associate color images to depth images based on the time stamp.
+    % Load time stamp data of color images
+    timeColor = helperImportTimestampFile([imageFolder, 'rgb.txt']);
+    
+    % Load time stamp data of depth images
+    timeDepth = helperImportTimestampFile([imageFolder, 'depth.txt']);
+    
+    % Align the time stamp
+    indexPairs = helperAlignTimestamp(timeColor, timeDepth);
+    
+    % Select the synchronized image data
+    imdsColor     = subset(imdsColor, indexPairs(:, 1));
+    imdsDepth     = subset(imdsDepth, indexPairs(:, 2));
+
+    % Process the image sequence
+    [worldPointSetOutput, optimizedPoses, pointCloudsAll] = ProcessImageSequence(imdsColor, imdsDepth);
+
+    % Save the outputs to .mat files
+    save('worldPointSetOutput.mat', 'worldPointSetOutput');
+    save('optimizedPoses.mat', 'optimizedPoses');
+    save('pointCloudsAll.mat', 'pointCloudsAll');
+
+end
+
+
+function [worldPointSetOutput, optimizedPoses, pointCloudsAll] = ProcessImageSequence(imdsColor, imdsDepth)
+    % Inspect the first RGB-D image
+    currFrameIdx  = 1;
+    currIcolor    = readimage(imdsColor, currFrameIdx);
+    currIdepth    = readimage(imdsDepth, currFrameIdx);
+    imshowpair(currIcolor, currIdepth, "montage");
+    
+    % Map Initialization: The pipeline starts by initializing the map that holds 3-D world points. 
+    % This step is crucial and has a significant impact on the accuracy of the final SLAM result. 
+    % Initial ORB feature points are extracted from the first color image using helperDetectAndExtractFeatures. 
+    % Their corresponding 3-D world locations can be computed from the pixel coordinates of the feature 
+    % points and the depth value using helperReconstructFromRGBD.
+
+    % Set random seed for reproducibility
+    rng(0);
+    
+    % Create a cameraIntrinsics object to store the camera intrinsic parameters.
+    % The intrinsics for the dataset can be found at the following page:
+    % https://vision.in.tum.de/data/datasets/rgbd-dataset/file_formats
+    focalLength    = [535.4, 539.2];    % in units of pixels
+    principalPoint = [320.1, 247.6];    % in units of pixels
+    imageSize      = size(currIcolor,[1,2]); % in pixels [mrows, ncols]
+    depthFactor    = 5e3;
+    intrinsics     = cameraIntrinsics(focalLength,principalPoint,imageSize);
+    
+    % Detect and extract ORB features from the color image
+    scaleFactor = 1.2;
+    numLevels   = 8;
+    [currFeatures, currPoints] = helperDetectAndExtractFeatures(currIcolor, scaleFactor, numLevels); 
+    
+    initialPose = rigidtform3d();
+    [xyzPoints, validIndex] = helperReconstructFromRGBD(currPoints, currIdepth, intrinsics, initialPose, depthFactor);
+
+    % Initialize Place Recognition Database
+    % Loop detection is performed using the bags-of-words approach. A visual vocabulary represented as a bagOfFeatures object is created offline with the ORB descriptors extracted from a large set of images in the dataset by calling:
+    % bag = bagOfFeatures(imds,CustomExtractor=@helperORBFeatureExtractorFunction, TreeProperties=[5, 10], StrongestFeatures=1);
+    % where imds is an imageDatastore object storing the training images and helperORBFeatureExtractorFunction is the ORB feature extractor function. See Image Retrieval with Bag of Visual Words for more information.
+    % The loop closure process incrementally builds a database, represented as an invertedImageIndex object, that stores the visual word-to-image mapping based on the bag of ORB features.
+
+    % Load the bag of features data created offline
+    bofData         = load("bagOfFeaturesDataSLAM.mat");
+    
+    % Initialize the place recognition database
+    loopDatabase    = invertedImageIndex(bofData.bof, SaveFeatureLocations=false);
+    
+    % Add features of the first key frame to the database
+    currKeyFrameId = 1;
+    addImageFeatures(loopDatabase, currFeatures, currKeyFrameId);
+
+    % Data Management and Visualization
+    % After the map is initialized using the first pair of color and depth image, you can use imageviewset and worldpointset to store the first key frames and the corresponding map points:
+
+    % Create an empty imageviewset object to store key frames
+    vSetKeyFrames = imageviewset;
+    
+    % Create an empty worldpointset object to store 3-D map points
+    mapPointSet   = worldpointset;
+    
+    % Add the first key frame
+    vSetKeyFrames = addView(vSetKeyFrames, currKeyFrameId, initialPose, Points=currPoints,...
+        Features=currFeatures.Features);
+    
+    % Add 3-D map points
+    [mapPointSet, rgbdMapPointsIdx] = addWorldPoints(mapPointSet, xyzPoints);
+    
+    % Add observations of the map points
+    mapPointSet = addCorrespondences(mapPointSet, currKeyFrameId, rgbdMapPointsIdx, validIndex);
+    
+    % Update view direction and depth
+    mapPointSet = updateLimitsAndDirection(mapPointSet, rgbdMapPointsIdx, vSetKeyFrames.Views);
+    
+    % Update representative view
+    mapPointSet = updateRepresentativeView(mapPointSet, rgbdMapPointsIdx, vSetKeyFrames.Views);
+    
+    % Visualize matched features in the first key frame
+    featurePlot = helperVisualizeMatchedFeaturesRGBD(currIcolor, currIdepth, currPoints(validIndex));
+    
+    % Visualize initial map points and camera trajectory
+    xLim = [-4 4];
+    yLim = [-3 1];
+    zLim = [-1 6];
+    mapPlot  = helperVisualizeMotionAndStructure(vSetKeyFrames, mapPointSet, xLim, yLim, zLim);
+    
+    % Show legend
+    showLegend(mapPlot);
+
+    % Tracking
+    % The tracking process is performed using every RGB-D image and determines when to insert a new key frame. 
+    % ViewId of the last key frame
+    lastKeyFrameId    = currKeyFrameId;
+    
+    % Index of the last key frame in the input image sequence
+    lastKeyFrameIdx   = currFrameIdx; 
+    
+    % Indices of all the key frames in the input image sequence
+    addedFramesIdx    = lastKeyFrameIdx;
+    
+    currFrameIdx      = 2;
+    isLoopClosed      = false;
+
+    % Each frame is processed as follows:
+    % ORB features are extracted for each new color image and then matched (using matchFeatures), with features in the last key frame that have known corresponding 3-D map points.
+    % Estimate the camera pose using Perspective-n-Point algorithm, which estimates the pose of a calibrated camera given a set of 3-D points and their corresponding 2-D projections using estworldpose.
+    % Given the camera pose, project the map points observed by the last key frame into the current frame and search for feature correspondences using  matchFeaturesInRadius.
+    % With 3-D to 2-D correspondences in the current frame, refine the camera pose by performing a motion-only bundle adjustment using bundleAdjustmentMotion.
+    % Project the local map points into the current frame to search for more feature correspondences using matchFeaturesInRadius and refine the camera pose again using bundleAdjustmentMotion.
+    % The last step of tracking is to decide if the current frame should be a new key frame. A frame is a key frame if both of the following conditions are satisfied:
+    % At least 20 frames have passed since the last key frame or the current frame tracks fewer than 100 map points or 25% of points tracked by the reference key frame.
+    % The map points tracked by the current frame are fewer than 90% of points tracked by the reference key frame.
+    % If the current frame is to become a key frame, continue to the Local Mapping process. Otherwise, start Tracking for the next frame.
+    
+    % Main loop
+    isLastFrameKeyFrame = true;
+    while ~isLoopClosed && currFrameIdx < numel(imdsColor.Files)
+    
+        currIcolor = readimage(imdsColor, currFrameIdx);
+        currIdepth = readimage(imdsDepth, currFrameIdx);
+    
+        [currFeatures, currPoints]    = helperDetectAndExtractFeatures(currIcolor, scaleFactor, numLevels);
+    
+        % Track the last key frame
+        % trackedMapPointsIdx:  Indices of the map points observed in the current left frame 
+        % trackedFeatureIdx:    Indices of the corresponding feature points in the current left frame
+        [currPose, trackedMapPointsIdx, trackedFeatureIdx] = helperTrackLastKeyFrame(mapPointSet, ...
+            vSetKeyFrames.Views, currFeatures, currPoints, lastKeyFrameId, intrinsics, scaleFactor);
+        
+        if isempty(currPose) || numel(trackedMapPointsIdx) < 30
+            currFrameIdx = currFrameIdx + 1;
+            continue
+        end
+        
+        % Track the local map and check if the current frame is a key frame.
+        % A frame is a key frame if both of the following conditions are satisfied:
+        %
+        % 1. At least 20 frames have passed since the last key frame or the 
+        %    current frame tracks fewer than 100 map points. 
+        % 2. The map points tracked by the current frame are fewer than 90% of 
+        %    points tracked by the reference key frame.
+        %
+        % localKeyFrameIds:   ViewId of the connected key frames of the current frame
+        numSkipFrames     = 20;
+        numPointsKeyFrame = 100;
+        [localKeyFrameIds, currPose, trackedMapPointsIdx, trackedFeatureIdx, isKeyFrame] = ...
+            helperTrackLocalMap(mapPointSet, vSetKeyFrames, trackedMapPointsIdx, ...
+            trackedFeatureIdx, currPose, currFeatures, currPoints, intrinsics, scaleFactor, numLevels, ...
+            isLastFrameKeyFrame, lastKeyFrameIdx, currFrameIdx, numSkipFrames, numPointsKeyFrame);
+    
+        % Visualize matched features
+        updatePlot(featurePlot, currIcolor, currIdepth, currPoints(trackedFeatureIdx));
+        
+        if ~isKeyFrame
+            currFrameIdx = currFrameIdx + 1;
+            isLastFrameKeyFrame = false;
+            continue
+        else
+            % Match feature points between the stereo images and get the 3-D world positions
+            [xyzPoints, validIndex] = helperReconstructFromRGBD(currPoints, currIdepth, ...
+                intrinsics, currPose, depthFactor);
+    
+            [untrackedFeatureIdx, ia] = setdiff(validIndex, trackedFeatureIdx);
+            xyzPoints = xyzPoints(ia, :);
+            isLastFrameKeyFrame = true;
+        end
+    
+        % Update current key frame ID
+        currKeyFrameId  = currKeyFrameId + 1;
+
+        % Local Mapping
+        % Local mapping is performed for every key frame. When a new key frame is determined, add it to the key frames and update the attributes of the map points observed by the new key frame. To ensure that mapPointSet contains as few outliers as possible, a valid map point must be observed in at least 3 key frames. 
+        % New map points are created by triangulating ORB feature points in the current key frame and its connected key frames. For each unmatched feature point in the current key frame, search for a match with other unmatched points in the connected key frames using matchFeatures. The local bundle adjustment refines the pose of the current key frame, the poses of connected key frames, and all the map points observed in these key frames.
+
+        % Add the new key frame    
+        [mapPointSet, vSetKeyFrames] = helperAddNewKeyFrame(mapPointSet, vSetKeyFrames, ...
+            currPose, currFeatures, currPoints, trackedMapPointsIdx, trackedFeatureIdx, localKeyFrameIds);
+            
+        % Remove outlier map points that are observed in fewer than 3 key frames
+        if currKeyFrameId == 2
+            triangulatedMapPointsIdx = [];
+        end
+        
+        [mapPointSet, trackedMapPointsIdx] = ...
+            helperCullRecentMapPoints(mapPointSet, trackedMapPointsIdx, triangulatedMapPointsIdx, ...
+            rgbdMapPointsIdx);
+        
+        % Add new map points computed from disparity 
+        [mapPointSet, rgbdMapPointsIdx] = addWorldPoints(mapPointSet, xyzPoints);
+        mapPointSet = addCorrespondences(mapPointSet, currKeyFrameId, rgbdMapPointsIdx, ...
+            untrackedFeatureIdx);
+        
+        % Create new map points by triangulation
+        minNumMatches = 10;
+        minParallax   = 0.35;
+        [mapPointSet, vSetKeyFrames, triangulatedMapPointsIdx, rgbdMapPointsIdx] = helperCreateNewMapPointsStereo( ...
+            mapPointSet, vSetKeyFrames, currKeyFrameId, intrinsics, scaleFactor, minNumMatches, minParallax, ...
+            untrackedFeatureIdx, rgbdMapPointsIdx);
+    
+        % Update view direction and depth
+        mapPointSet = updateLimitsAndDirection(mapPointSet, [triangulatedMapPointsIdx; rgbdMapPointsIdx], ...
+            vSetKeyFrames.Views);
+    
+        % Update representative view
+        mapPointSet = updateRepresentativeView(mapPointSet, [triangulatedMapPointsIdx; rgbdMapPointsIdx], ...
+            vSetKeyFrames.Views);
+    
+        % Local bundle adjustment
+        [mapPointSet, vSetKeyFrames, triangulatedMapPointsIdx, rgbdMapPointsIdx] = ...
+            helperLocalBundleAdjustmentStereo(mapPointSet, vSetKeyFrames, ...
+            currKeyFrameId, intrinsics, triangulatedMapPointsIdx, rgbdMapPointsIdx);
+
+        % Check if the KeyFrames directory exists; if not, create it
+        keyFramesDir = './KeyFrames';
+        if ~exist(keyFramesDir, 'dir')
+            mkdir(keyFramesDir);
+        end
+
+        % Store feature locations for this key frame
+        keyFramePointsDir = './KeyFramePoints';
+        if ~exist(keyFramePointsDir, 'dir')
+            mkdir(keyFramePointsDir); 
+        end
+
+        % Save the current key frame image using currKeyFrameId
+        filename = sprintf('%s/KeyFrame_%04d.png', keyFramesDir, currKeyFrameId);
+        imwrite(currIcolor, filename);
+
+        % Save feature points information
+        saveKeyFramePoints(keyFramePointsDir, currKeyFrameId, currPoints(trackedFeatureIdx), trackedMapPointsIdx);
+    
+        % Visualize 3-D world points and camera trajectory
+        updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
+
+        % Loop Closure
+        % The loop closure detection step takes the current key frame processed by the local mapping process and tries to detect and close the loop. Loop candidates are identified by querying images in the database that are visually similar to the current key frame using evaluateImageRetrieval. A candidate key frame is valid if it is not connected to the last key frame and three of its neighbor key frames are loop candidates.
+        % When a valid loop candidate is found, use estgeotform3d to compute the relative pose between the loop candidate frame and the current key frame. The relative pose represents a 3-D rigid transformation stored in a rigidtform3d object. Then add the loop connection with the relative pose and update mapPointSet and vSetKeyFrames.
+        % Check loop closure after some key frames have been created    
+        if currKeyFrameId > 20
+            
+            % Minimum number of feature matches of loop edges
+            loopEdgeNumMatches = 120;
+            
+            % Detect possible loop closure key frame candidates
+            [isDetected, validLoopCandidates] = helperCheckLoopClosure(vSetKeyFrames, currKeyFrameId, ...
+                loopDatabase, currIcolor, loopEdgeNumMatches);
+            
+            if isDetected 
+                % Add loop closure connections
+                maxDistance = 0.1;
+                [isLoopClosed, mapPointSet, vSetKeyFrames] = helperAddLoopConnectionsStereo(...
+                    mapPointSet, vSetKeyFrames, validLoopCandidates, currKeyFrameId, ...
+                    currFeatures, currPoints, loopEdgeNumMatches, maxDistance);
+            end
+        end
+        
+        % If no loop closure is detected, add current features into the database
+        if ~isLoopClosed
+            addImageFeatures(loopDatabase,  currFeatures, currKeyFrameId);
+        end
+        
+        % Update IDs and indices
+        lastKeyFrameId  = currKeyFrameId;
+        lastKeyFrameIdx = currFrameIdx;
+        addedFramesIdx  = [addedFramesIdx; currFrameIdx]; %#ok<AGROW>
+        currFrameIdx    = currFrameIdx + 1;
+    end % End of main loop
+
+    % Finally, apply pose graph optimization over the essential graph in vSetKeyFrames to correct the drift. The essential graph is created internally by removing connections with fewer than minNumMatches matches in the covisibility graph. After pose graph optimization, update the 3-D locations of the map points using the optimized poses.
+    
+    % Optimize the poses
+    minNumMatches      = 50;
+    vSetKeyFramesOptim = optimizePoses(vSetKeyFrames, minNumMatches, Tolerance=1e-16);
+    
+    % Update map points after optimizing the poses
+    mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim);
+    
+    updatePlot(mapPlot, vSetKeyFrames, mapPointSet);
+    
+    % Plot the optimized camera trajectory
+    optimizedPoses  = poses(vSetKeyFramesOptim);
+    plotOptimizedTrajectory(mapPlot, optimizedPoses)
+    
+    % Update legend
+    showLegend(mapPlot);
+
+    worldPointSetOutput = mapPointSet;
+
+    % Dense Reconstruction from Depth Image
+    % Given the refined camera poses, you can reproject all the valid image points in the associated depth images back to the 3-D space to perform dense reconstruction. 
+    % Create an array of pointCloud objects to store the world points constructed
+
+    % from the key frames
+    ptClouds =  repmat(pointCloud(zeros(1, 3)), numel(addedFramesIdx), 1);
+    
+    % Ignore image points at the boundary 
+    offset = 40;
+    [X, Y] = meshgrid(offset:2:imageSize(2)-offset, offset:2:imageSize(1)-offset);
+    
+    for i = 1: numel(addedFramesIdx)
+        Icolor = readimage(imdsColor, addedFramesIdx(i));
+        Idepth = readimage(imdsDepth, addedFramesIdx(i));
+    
+        [xyzPoints, validIndex] = helperReconstructFromRGBD([X(:), Y(:)], ...
+            Idepth, intrinsics, optimizedPoses.AbsolutePose(i), depthFactor);
+    
+        colors = zeros(numel(X), 1, 'like', Icolor);
+        for j = 1:numel(X)
+            colors(j, 1:3) = Icolor(Y(j), X(j), :);
+        end
+        ptClouds(i) = pointCloud(xyzPoints, Color=colors(validIndex, :));
+    end
+    
+    % Concatenate the point clouds
+    pointCloudsAll = pccat(ptClouds);
+    
+    figure
+    pcshow(pointCloudsAll,VerticalAxis="y", VerticalAxisDir="down");
+    xlabel('X')
+    ylabel('Y')
+    zlabel('Z')
+end
+
+%% Helper functions
+
+% helperImportTimestampFile Import time stamp file
+
+function timestamp = helperImportTimestampFile(filename)
+    % Input handling
+    dataLines = [4, Inf];
+    
+    %% Set up the Import Options and import the data
+    opts = delimitedTextImportOptions("NumVariables", 2);
+    
+    % Specify range and delimiter
+    opts.DataLines = dataLines;
+    opts.Delimiter = " ";
+    
+    % Specify column names and types
+    opts.VariableNames = ["VarName1", "Var2"];
+    opts.SelectedVariableNames = "VarName1";
+    opts.VariableTypes = ["double", "string"];
+    
+    % Specify file level properties
+    opts.ExtraColumnsRule = "ignore";
+    opts.EmptyLineRule = "read";
+    opts.ConsecutiveDelimitersRule = "join";
+    opts.LeadingDelimitersRule = "ignore";
+    
+    % Specify variable properties
+    opts = setvaropts(opts, "Var2", "WhitespaceRule", "preserve");
+    opts = setvaropts(opts, "Var2", "EmptyFieldRule", "auto");
+    
+    % Import the data
+    data = readtable(filename, opts);
+    
+    % Convert to output type
+    timestamp = table2array(data);
+end
+
+% helperAlignTimestamp align time stamp of color and depth images.
+function indexPairs = helperAlignTimestamp(timeColor, timeDepth)
+    idxDepth = 1;
+    indexPairs = zeros(numel(timeColor), 2);
+    for i = 1:numel(timeColor)
+        for j = idxDepth : numel(timeDepth)
+            if abs(timeColor(i) - timeDepth(j)) < 1e-4
+                idxDepth = j;
+                indexPairs(i, :) = [i, j];
+                break
+            elseif timeDepth(j) - timeColor(i) > 1e-3
+                break
+            end
+        end
+    end
+    indexPairs = indexPairs(indexPairs(:,1)>0, :);
+end
+
+% helperDetectAndExtractFeatures detect and extract and ORB features from the image.
+function [features, validPoints] = helperDetectAndExtractFeatures(Irgb, scaleFactor, numLevels)
+ 
+    numPoints = 1000;
+    
+    % Detect ORB features
+    Igray  = rgb2gray(Irgb);
+    
+    points = detectORBFeatures(Igray, ScaleFactor=scaleFactor, NumLevels=numLevels);
+    
+    % Select a subset of features, uniformly distributed throughout the image
+    points = selectUniform(points, numPoints, size(Igray, 1:2));
+    
+    % Extract features
+    [features, validPoints] = extractFeatures(Igray, points);
+end
+
+% helperReconstructFromRGBD reconstruct scene from color and depth image.
+
+function [xyzPoints, validIndex] = helperReconstructFromRGBD(points, ...
+    depthMap, intrinsics, currPose, depthFactor)
+
+    ptcloud = pcfromdepth(depthMap,depthFactor,intrinsics,ImagePoints=points, DepthRange=[0.1, 5]);
+    
+    isPointValid = ~isnan(ptcloud.Location(:, 1));
+    xyzPoints    = ptcloud.Location(isPointValid, :);
+    xyzPoints    = transformPointsForward(currPose, xyzPoints);
+    validIndex   = find(isPointValid);
+end
+
+% helperCullRecentMapPoints cull recently added map points.
+function [mapPointSet, mapPointsIdx] = ...
+    helperCullRecentMapPoints(mapPointSet, mapPointsIdx, newPointIdx, rgbdMapPointsIndices)
+    outlierIdx = setdiff([newPointIdx; rgbdMapPointsIndices], mapPointsIdx);
+    if ~isempty(outlierIdx)
+        mapPointSet   = removeWorldPoints(mapPointSet, outlierIdx);
+        mapPointsIdx  = mapPointsIdx - arrayfun(@(x) nnz(x>outlierIdx), mapPointsIdx);
+    end
+end
+
+% helperEstimateTrajectoryError calculate the tracking error.
+function rmse = helperEstimateTrajectoryError(gTruth, cameraPoses)
+    locations       = vertcat(cameraPoses.AbsolutePose.Translation);
+    gLocations      = vertcat(gTruth.Translation);
+    scale           = median(vecnorm(gLocations, 2, 2))/ median(vecnorm(locations, 2, 2));
+    scaledLocations = locations * scale;
+    
+    rmse = sqrt(mean( sum((scaledLocations - gLocations).^2, 2) ));
+    disp(['Absolute RMSE for key frame trajectory (m): ', num2str(rmse)]);
+end
+
+% helperUpdateGlobalMap update 3-D locations of map points after pose graph optimization
+function mapPointSet = helperUpdateGlobalMap(mapPointSet, vSetKeyFrames, vSetKeyFramesOptim)
+
+    posesOld     = vSetKeyFrames.Views.AbsolutePose;
+    posesNew     = vSetKeyFramesOptim.Views.AbsolutePose;
+    positionsOld = mapPointSet.WorldPoints;
+    positionsNew = positionsOld;
+    indices = 1:mapPointSet.Count;
+    
+    % Update world location of each map point based on the new absolute pose of 
+    % the corresponding major view
+    for i = 1: mapPointSet.Count
+        majorViewIds = mapPointSet.RepresentativeViewId(i);
+        tform = rigidtform3d(posesNew(majorViewIds).A/posesOld(majorViewIds).A);
+        positionsNew(i, :) = transformPointsForward(tform, positionsOld(i, :));
+    end
+    mapPointSet = updateWorldPoints(mapPointSet, indices, positionsNew);
+end
+
+% CSV file creation for points within keyframe
+function saveKeyFramePoints(dirPath, keyFrameId, featurePoints, mapPointsIdx)
+    % Ensure the directory exists
+    if ~exist(dirPath, 'dir')
+        mkdir(dirPath);
+    end
+
+    % Define the filename for the CSV file
+    csvFilename = sprintf('%s/KeyFramePoints_%04d.csv', dirPath, keyFrameId);
+
+    % Extract pixel locations from the feature points
+    pixelLocations = featurePoints.Location;  % This should be an Nx2 matrix
+
+    % Combine the indices, pixel locations, and corresponding world points indices into one matrix
+    dataMatrix = [pixelLocations, mapPointsIdx];  % Concatenate horizontally
+
+    % Write the combined data to a CSV file
+    writematrix(dataMatrix, csvFilename);
+end
diff --git a/target/classes/vslam/worldPointSet 2.mat b/target/classes/vslam/worldPointSet 2.mat
new file mode 100644
index 0000000000000000000000000000000000000000..3a558ef8f87d8d98b9cfabb5c53678ee110e06cf
Binary files /dev/null and b/target/classes/vslam/worldPointSet 2.mat differ
diff --git a/target/classes/vslam/worldPointSet.mat b/target/classes/vslam/worldPointSet.mat
new file mode 100644
index 0000000000000000000000000000000000000000..3a558ef8f87d8d98b9cfabb5c53678ee110e06cf
Binary files /dev/null and b/target/classes/vslam/worldPointSet.mat differ
diff --git a/target/classes/vslam/worldPointSetOutput.mat b/target/classes/vslam/worldPointSetOutput.mat
new file mode 100644
index 0000000000000000000000000000000000000000..383fec4a6a1c781837ee0bf0e9b0d4aa65556141
Binary files /dev/null and b/target/classes/vslam/worldPointSetOutput.mat differ
diff --git a/target/classes/yolo/YOLODetector.class b/target/classes/yolo/YOLODetector.class
new file mode 100644
index 0000000000000000000000000000000000000000..da1302ef1aca9aa03dd538781f27d001bff5021b
Binary files /dev/null and b/target/classes/yolo/YOLODetector.class differ
diff --git a/target/classes/yolo/YOLONet$ObjectDetectionResult.class b/target/classes/yolo/YOLONet$ObjectDetectionResult.class
new file mode 100644
index 0000000000000000000000000000000000000000..c8b1ef244916f4a2932492116af111dfe15470d9
Binary files /dev/null and b/target/classes/yolo/YOLONet$ObjectDetectionResult.class differ
diff --git a/target/classes/yolo/YOLONet.class b/target/classes/yolo/YOLONet.class
new file mode 100644
index 0000000000000000000000000000000000000000..759fae0f5a60d8420cd1245a042c5eb496187db5
Binary files /dev/null and b/target/classes/yolo/YOLONet.class differ
diff --git a/target/classes/yolo/coco.names b/target/classes/yolo/coco.names
new file mode 100644
index 0000000000000000000000000000000000000000..16315f2becec9705017bfaf1b9fb81ca2a83c0b0
--- /dev/null
+++ b/target/classes/yolo/coco.names
@@ -0,0 +1,80 @@
+person
+bicycle
+car
+motorbike
+aeroplane
+bus
+train
+truck
+boat
+traffic light
+fire hydrant
+stop sign
+parking meter
+bench
+bird
+cat
+dog
+horse
+sheep
+cow
+elephant
+bear
+zebra
+giraffe
+backpack
+umbrella
+handbag
+tie
+suitcase
+frisbee
+skis
+snowboard
+sports ball
+kite
+baseball bat
+baseball glove
+skateboard
+surfboard
+tennis racket
+bottle
+wine glass
+cup
+fork
+knife
+spoon
+bowl
+banana
+apple
+sandwich
+orange
+broccoli
+carrot
+hot dog
+pizza
+donut
+cake
+chair
+sofa
+pottedplant
+bed
+diningtable
+toilet
+tvmonitor
+laptop
+mouse
+remote
+keyboard
+cell phone
+microwave
+oven
+toaster
+sink
+refrigerator
+book
+clock
+vase
+scissors
+teddy bear
+hair drier
+toothbrush
\ No newline at end of file
diff --git a/target/classes/yolo/yolov4.cfg b/target/classes/yolo/yolov4.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..2985a313f610e032732e388ca6d0a7729ae7f267
--- /dev/null
+++ b/target/classes/yolo/yolov4.cfg
@@ -0,0 +1,1157 @@
+[net]
+batch=64
+subdivisions=8
+# Training
+#width=512
+#height=512
+width=608
+height=608
+channels=3
+momentum=0.949
+decay=0.0005
+angle=0
+saturation = 1.5
+exposure = 1.5
+hue=.1
+
+learning_rate=0.0013
+burn_in=1000
+max_batches = 500500
+policy=steps
+steps=400000,450000
+scales=.1,.1
+
+#cutmix=1
+mosaic=1
+
+#:104x104 54:52x52 85:26x26 104:13x13 for 416
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-7
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-10
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-28
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-28
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-16
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=1
+stride=1
+pad=1
+activation=mish
+
+##########################
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+### SPP ###
+[maxpool]
+stride=1
+size=5
+
+[route]
+layers=-2
+
+[maxpool]
+stride=1
+size=9
+
+[route]
+layers=-4
+
+[maxpool]
+stride=1
+size=13
+
+[route]
+layers=-1,-3,-5,-6
+### End SPP ###
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = 85
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -1, -3
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = 54
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -1, -3
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=256
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=256
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+##########################
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=256
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 0,1,2
+anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+scale_x_y = 1.2
+iou_thresh=0.213
+cls_normalizer=1.0
+iou_normalizer=0.07
+iou_loss=ciou
+nms_kind=greedynms
+beta_nms=0.6
+max_delta=5
+
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=2
+pad=1
+filters=256
+activation=leaky
+
+[route]
+layers = -1, -16
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 3,4,5
+anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+scale_x_y = 1.1
+iou_thresh=0.213
+cls_normalizer=1.0
+iou_normalizer=0.07
+iou_loss=ciou
+nms_kind=greedynms
+beta_nms=0.6
+max_delta=5
+
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=2
+pad=1
+filters=512
+activation=leaky
+
+[route]
+layers = -1, -37
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 6,7,8
+anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+scale_x_y = 1.05
+iou_thresh=0.213
+cls_normalizer=1.0
+iou_normalizer=0.07
+iou_loss=ciou
+nms_kind=greedynms
+beta_nms=0.6
+max_delta=5
diff --git a/target/classes/yolo/yolov4.weights b/target/classes/yolo/yolov4.weights
new file mode 100644
index 0000000000000000000000000000000000000000..921f4406ecaa54a53031dd695e7bcd96f5dd9be2
Binary files /dev/null and b/target/classes/yolo/yolov4.weights differ
diff --git a/target/test-classes/.DS_Store b/target/test-classes/.DS_Store
new file mode 100644
index 0000000000000000000000000000000000000000..aa365cbfad50e612896ac93c289d4a02efa65659
Binary files /dev/null and b/target/test-classes/.DS_Store differ
diff --git a/target/test-classes/object_detection/BoundingBoxTests.class b/target/test-classes/object_detection/BoundingBoxTests.class
new file mode 100644
index 0000000000000000000000000000000000000000..4fd7ec9e65bfec2a264989b37ff19d1183fecc8b
Binary files /dev/null and b/target/test-classes/object_detection/BoundingBoxTests.class differ
diff --git a/target/test-classes/object_detection/ObjectSetTests.class b/target/test-classes/object_detection/ObjectSetTests.class
new file mode 100644
index 0000000000000000000000000000000000000000..bd4f79feabcfd3e9de11047fbdc4b7afd08edc2d
Binary files /dev/null and b/target/test-classes/object_detection/ObjectSetTests.class differ
diff --git a/target/test-classes/object_detection/PointTests.class b/target/test-classes/object_detection/PointTests.class
new file mode 100644
index 0000000000000000000000000000000000000000..40ded9809bea2d1e8c7c644e32828eff0909c437
Binary files /dev/null and b/target/test-classes/object_detection/PointTests.class differ
diff --git a/target/test-classes/yolo/.gitkeep b/target/test-classes/yolo/.gitkeep
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/target/test-classes/yolo/.gitkeep 2 b/target/test-classes/yolo/.gitkeep 2
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/target/test-classes/yolo/KeyFrame_0060 2.csv b/target/test-classes/yolo/KeyFrame_0060 2.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bd8544564a0d5fc5972a6dc8cc6b5b8ef7b6e8e5
--- /dev/null
+++ b/target/test-classes/yolo/KeyFrame_0060 2.csv	
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.966170,187,292,78,65
+tvmonitor,0.911748,64,-2,228,136
+keyboard,0.845111,25,113,245,130
diff --git a/target/test-classes/yolo/KeyFrame_0060.csv b/target/test-classes/yolo/KeyFrame_0060.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bd8544564a0d5fc5972a6dc8cc6b5b8ef7b6e8e5
--- /dev/null
+++ b/target/test-classes/yolo/KeyFrame_0060.csv
@@ -0,0 +1,4 @@
+Class,Confidence,X,Y,Width,Height
+mouse,0.966170,187,292,78,65
+tvmonitor,0.911748,64,-2,228,136
+keyboard,0.845111,25,113,245,130
diff --git a/target/test-classes/yolo/TestFrame 2.png b/target/test-classes/yolo/TestFrame 2.png
new file mode 100644
index 0000000000000000000000000000000000000000..3886bb1a0f80d4fb37fe4c30ca3a22fca4199216
Binary files /dev/null and b/target/test-classes/yolo/TestFrame 2.png differ
diff --git a/target/test-classes/yolo/TestFrame.png b/target/test-classes/yolo/TestFrame.png
new file mode 100644
index 0000000000000000000000000000000000000000..3886bb1a0f80d4fb37fe4c30ca3a22fca4199216
Binary files /dev/null and b/target/test-classes/yolo/TestFrame.png differ
diff --git a/target/test-classes/yolo/YOLOTest 2.class b/target/test-classes/yolo/YOLOTest 2.class
new file mode 100644
index 0000000000000000000000000000000000000000..e6d61d4eca2c47f98ec4ac414d0da4db5ab1ef91
Binary files /dev/null and b/target/test-classes/yolo/YOLOTest 2.class differ
diff --git a/target/test-classes/yolo/YOLOTest.class b/target/test-classes/yolo/YOLOTest.class
new file mode 100644
index 0000000000000000000000000000000000000000..e6d61d4eca2c47f98ec4ac414d0da4db5ab1ef91
Binary files /dev/null and b/target/test-classes/yolo/YOLOTest.class differ
diff --git a/target/test-classes/yolo/coco.names b/target/test-classes/yolo/coco.names
new file mode 100644
index 0000000000000000000000000000000000000000..16315f2becec9705017bfaf1b9fb81ca2a83c0b0
--- /dev/null
+++ b/target/test-classes/yolo/coco.names
@@ -0,0 +1,80 @@
+person
+bicycle
+car
+motorbike
+aeroplane
+bus
+train
+truck
+boat
+traffic light
+fire hydrant
+stop sign
+parking meter
+bench
+bird
+cat
+dog
+horse
+sheep
+cow
+elephant
+bear
+zebra
+giraffe
+backpack
+umbrella
+handbag
+tie
+suitcase
+frisbee
+skis
+snowboard
+sports ball
+kite
+baseball bat
+baseball glove
+skateboard
+surfboard
+tennis racket
+bottle
+wine glass
+cup
+fork
+knife
+spoon
+bowl
+banana
+apple
+sandwich
+orange
+broccoli
+carrot
+hot dog
+pizza
+donut
+cake
+chair
+sofa
+pottedplant
+bed
+diningtable
+toilet
+tvmonitor
+laptop
+mouse
+remote
+keyboard
+cell phone
+microwave
+oven
+toaster
+sink
+refrigerator
+book
+clock
+vase
+scissors
+teddy bear
+hair drier
+toothbrush
\ No newline at end of file
diff --git a/target/test-classes/yolo/yolov4 2.cfg b/target/test-classes/yolo/yolov4 2.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..2985a313f610e032732e388ca6d0a7729ae7f267
--- /dev/null
+++ b/target/test-classes/yolo/yolov4 2.cfg	
@@ -0,0 +1,1157 @@
+[net]
+batch=64
+subdivisions=8
+# Training
+#width=512
+#height=512
+width=608
+height=608
+channels=3
+momentum=0.949
+decay=0.0005
+angle=0
+saturation = 1.5
+exposure = 1.5
+hue=.1
+
+learning_rate=0.0013
+burn_in=1000
+max_batches = 500500
+policy=steps
+steps=400000,450000
+scales=.1,.1
+
+#cutmix=1
+mosaic=1
+
+#:104x104 54:52x52 85:26x26 104:13x13 for 416
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-7
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-10
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-28
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-28
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-16
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=1
+stride=1
+pad=1
+activation=mish
+
+##########################
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+### SPP ###
+[maxpool]
+stride=1
+size=5
+
+[route]
+layers=-2
+
+[maxpool]
+stride=1
+size=9
+
+[route]
+layers=-4
+
+[maxpool]
+stride=1
+size=13
+
+[route]
+layers=-1,-3,-5,-6
+### End SPP ###
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = 85
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -1, -3
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = 54
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -1, -3
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=256
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=256
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+##########################
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=256
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 0,1,2
+anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+scale_x_y = 1.2
+iou_thresh=0.213
+cls_normalizer=1.0
+iou_normalizer=0.07
+iou_loss=ciou
+nms_kind=greedynms
+beta_nms=0.6
+max_delta=5
+
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=2
+pad=1
+filters=256
+activation=leaky
+
+[route]
+layers = -1, -16
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 3,4,5
+anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+scale_x_y = 1.1
+iou_thresh=0.213
+cls_normalizer=1.0
+iou_normalizer=0.07
+iou_loss=ciou
+nms_kind=greedynms
+beta_nms=0.6
+max_delta=5
+
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=2
+pad=1
+filters=512
+activation=leaky
+
+[route]
+layers = -1, -37
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 6,7,8
+anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+scale_x_y = 1.05
+iou_thresh=0.213
+cls_normalizer=1.0
+iou_normalizer=0.07
+iou_loss=ciou
+nms_kind=greedynms
+beta_nms=0.6
+max_delta=5
diff --git a/target/test-classes/yolo/yolov4.cfg b/target/test-classes/yolo/yolov4.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..2985a313f610e032732e388ca6d0a7729ae7f267
--- /dev/null
+++ b/target/test-classes/yolo/yolov4.cfg
@@ -0,0 +1,1157 @@
+[net]
+batch=64
+subdivisions=8
+# Training
+#width=512
+#height=512
+width=608
+height=608
+channels=3
+momentum=0.949
+decay=0.0005
+angle=0
+saturation = 1.5
+exposure = 1.5
+hue=.1
+
+learning_rate=0.0013
+burn_in=1000
+max_batches = 500500
+policy=steps
+steps=400000,450000
+scales=.1,.1
+
+#cutmix=1
+mosaic=1
+
+#:104x104 54:52x52 85:26x26 104:13x13 for 416
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=3
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=32
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-7
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=64
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-10
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-28
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-28
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+# Downsample
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=3
+stride=2
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -2
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=3
+stride=1
+pad=1
+activation=mish
+
+[shortcut]
+from=-3
+activation=linear
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=mish
+
+[route]
+layers = -1,-16
+
+[convolutional]
+batch_normalize=1
+filters=1024
+size=1
+stride=1
+pad=1
+activation=mish
+
+##########################
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+### SPP ###
+[maxpool]
+stride=1
+size=5
+
+[route]
+layers=-2
+
+[maxpool]
+stride=1
+size=9
+
+[route]
+layers=-4
+
+[maxpool]
+stride=1
+size=13
+
+[route]
+layers=-1,-3,-5,-6
+### End SPP ###
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = 85
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -1, -3
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[upsample]
+stride=2
+
+[route]
+layers = 54
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[route]
+layers = -1, -3
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=256
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=256
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=128
+size=1
+stride=1
+pad=1
+activation=leaky
+
+##########################
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=256
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 0,1,2
+anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+scale_x_y = 1.2
+iou_thresh=0.213
+cls_normalizer=1.0
+iou_normalizer=0.07
+iou_loss=ciou
+nms_kind=greedynms
+beta_nms=0.6
+max_delta=5
+
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=2
+pad=1
+filters=256
+activation=leaky
+
+[route]
+layers = -1, -16
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=256
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=512
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 3,4,5
+anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+scale_x_y = 1.1
+iou_thresh=0.213
+cls_normalizer=1.0
+iou_normalizer=0.07
+iou_loss=ciou
+nms_kind=greedynms
+beta_nms=0.6
+max_delta=5
+
+
+[route]
+layers = -4
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=2
+pad=1
+filters=512
+activation=leaky
+
+[route]
+layers = -1, -37
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+filters=512
+size=1
+stride=1
+pad=1
+activation=leaky
+
+[convolutional]
+batch_normalize=1
+size=3
+stride=1
+pad=1
+filters=1024
+activation=leaky
+
+[convolutional]
+size=1
+stride=1
+pad=1
+filters=255
+activation=linear
+
+
+[yolo]
+mask = 6,7,8
+anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+scale_x_y = 1.05
+iou_thresh=0.213
+cls_normalizer=1.0
+iou_normalizer=0.07
+iou_loss=ciou
+nms_kind=greedynms
+beta_nms=0.6
+max_delta=5
diff --git a/target/test-classes/yolo/yolov4.weights b/target/test-classes/yolo/yolov4.weights
new file mode 100644
index 0000000000000000000000000000000000000000..921f4406ecaa54a53031dd695e7bcd96f5dd9be2
Binary files /dev/null and b/target/test-classes/yolo/yolov4.weights differ