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Description: shi-tomasi-good-features-cvpr1994 good features track---image proce
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Size: 250880 |
Author: fang hua |
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Description: Lucas-Kanader-Tomasi Feature Tracker，基于B.D.Lucas和T.Kanade[1]于1981的早期工作，于1991年由C.Tomasi和T.Kanade[2]完整导出，并于1994年由J.Shi和C.Tomasi[3]在文章中清楚地阐述。J.Y.Bougue[4]于2000年给出了此算法的一种实现，并收录在Intel公司的计算机视觉函数库OpenCV中。本例是此算法基于OpenCv的代码实现-Lucas-Kanader-Tomasi Feature Tracker, based on BDLucas and T. Kanade [1] in 1981 the early work, in 1991 by C. Tomasi and T. Kanade [2] a complete export, and was established in 1994 by J. Shi and C . Tomasi [3] in the article clearly explained. JYBougue [4] in 2000, given a realization of this algorithm and is included in Intel s computer vision library OpenCV in. This case is that this algorithm is based on the code OpenCv
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Size: 38208512 |
Author: 梁霄 |
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Description: We extend the well-known Shi-Tomasi-Kanade tracker by introducing an automatic scheme for rejecting spurious features. We employ a simple and efficient outlier rejection rule, called X84. Experiments with real and synthetic images confirm that our algorithm makes good features to track better
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Size: 90112 |
Author: tubeo |
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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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Description: The file contains Lucas-Kanade Tracker with pyramid and iteration to improve performance. There is a wrapper for image sequences, and a corner detection function using Shi-Tomasi method.
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Size: 6144 |
Author: 幽灵 |
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Description: vs2010+opencv，创建Harris和Shi-Tomasi检测器，检测输入图像中的特征点-vs2010+opencv, create Harris and Shi-Tomasi detector detects feature points in the input image
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Size: 2696192 |
Author: YYT |
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