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Description: source code and ref manual of KLT. KLT is an implementation, in the C programming language, of a feature tracker for the computer vision community. -source code and manual of KLT ref. KLT is an i mplementation. in the C programming language, a feature of tracker for the computer vision com munity.
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Author: jft987msn |
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Description: source code and ref manual of KLT. KLT is an implementation, in the C programming language, of a feature tracker for the computer vision community. -source code and manual of KLT ref. KLT is an i mplementation. in the C programming language, a feature of tracker for the computer vision com munity.
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Author: jft987msn |
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Description: Kanade-Lucas-Tomasi Feature Tracker,用于实现图像目标跟踪算法。-Kanade-Lucas-Tomasi Feature Tracker, used to realize the image target tracking algorithm.
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Size: 666624 |
Author: 梁潇 |
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Description: KLT: An Implementation of the
Kanade-Lucas-Tomasi Feature Tracker
KLT : An Implementation of the
Kanade-Lucas-Tomasi Feature Tracker -KLT: An Implementation of the
Kanade-Lucas-Tomasi Feature Tracker
KLT: An Implementation of the
Kanade-Lucas-Tomasi Feature Tracker
KLT: An Implementation of the
Kanade-Lucas-Tomasi Feature Tracker
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Author: zhou |
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Description: Deaf people use facial expressions a non-manual channel for conveying grammatical information in sign language. Tracking facial features using the Kanade - Lucas - Tomasi (KLT) algorithm is a simple and effective method toward recognizing these facial expressions, which are performed simultaneously with head motions and hand signs. To make the tracker robust under these conditions, a Bayesian framework was developed as a feedback mechanism to the KLT tracker. This mechanism relies on a set of face shape subspaces learned by Probabilistic Principal Component Analysis. An update scheme was utilized to modify these subspaces and adapt to persons with different face shapes. The result shows that the proposed system can track facial features with large head motions, substantial facial deformations, and temporary face occlusions by hand.-Deaf people use facial expressions as a non-manual channel for conveying grammatical information in sign language. Tracking facial features using the Kanade- Lucas- Tomasi (KLT) algorithm is a simple and effective method toward recognizing these facial expressions, which are performed simultaneously with head motions and hand signs. To make the tracker robust under these conditions, a Bayesian framework was developed as a feedback mechanism to the KLT tracker. This mechanism relies on a set of face shape subspaces learned by Probabilistic Principal Component Analysis. An update scheme was utilized to modify these subspaces and adapt to persons with different face shapes. The result shows that the proposed system can track facial features with large head motions, substantial facial deformations, and temporary face occlusions by hand.
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Size: 189440 |
Author: Ng Jack |
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Description: KLT tracker image processing
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Size: 4096 |
Author: saaman |
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Description: The KLT Tracker algorithm implementation. The starting location of the object must be manually initialized. Object tracking is accomplished using two methods: simple track and advanced track.
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Author: nablanc |
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Description: KLT is an implementation, in the C programming language, of a feature tracker for the computer vision community. The source code is in the public domain, available for both commercial and non-commerical use.-KLT is an implementation, in the C programming language, of a feature tracker for the computer vision community. The source code is in the public domain, available for both commercial and non-commerical use.
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Size: 684032 |
Author: 安新 |
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Description: it Detects the corners in any image to be tracked using other algorithms like KLT Tracker,SIFT,-it Detects the corners in any image to be tracked using other algorithms like KLT Tracker,SIFT,...
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Author: red |
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Description: KLT tracker using pyramid flow
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Author: red |
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Description: 这是KLT算法论文的高清版。Kanade-Lucas-Tomasi方法，在跟踪方面表现的也不错，尤其在实时计算速度上，用它来得到的，是很多点的轨迹“trajectory”，并且还有一些发生了漂移的点，所以，得到跟踪点之后要进行一些后期的处理，说到Kanade-Lucas-Tomasi方法，首先要追溯到Kanade-Lucas两人在上世纪80年代发表的paper：An Iterative Image Registration Technique with an Application to Stereo Vision，这里讲的是一种图像点定位的方法，即图像的局部匹配，将图像匹配问题，从传统的滑动窗口搜索方法变为一个求解偏移量d的过程，后来Jianbo Shi和Carlo Tomasi两人发表了一篇CVPR(94 )的文章Good Features To Track，这篇文章，主要就是讲，在求解d的过程中，哪些情况下可以保证一定能够得到d的解，这些情况的点有什么特点（后来会发现，很多时候都是寻找的角点）。-KLT is an implementation, in the C programming language, of a feature tracker for the computer vision community. The source code is in the public domain, available for both commercial and non-commerical use.
The tracker is based on the early work of Lucas and Kanade [1], was developed fully by Tomasi and Kanade [2], and was explained clearly in the paper by Shi and Tomasi [3]. Later, Tomasi proposed a slight modification which makes the computation symmetric with respect to the two images-- the resulting equation is derived in the unpublished note by myself [4]. Briefly, good features are located by examining the minimum eigenvalue of each 2 by 2 gradient matrix, and features are tracked using a Newton-Raphson method of minimizing the difference between the two windows. Multiresolution tracking allows for relatively large displacements between images. The affine computation that evaluates the consistency of features between non-consecutive frames [3] was implemented by Thorsten T
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Size: 789504 |
Author: 王凯 |
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