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Video tracking using Adaboost algorithm for auto-updating of the weak classifiers.
The object has to be defined by the user (no auto-recogntion). The tracker works for every type of object (no prior assumptions are taken to object size or form).
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里面是10篇关于智能视频监控中运动目标检测，识别，跟踪等的文章，还包含了两篇关于人运动检测识别的综述，希望对大家能有所帮助。-There is a 10 on the intelligent video surveillance in moving target detection, identification, tracking and other articles, also includes two on human motion detection to identify a synt
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包含M文件，培训和跟踪落实的噪音中描述的算法：
[1] J.S.厄克伦斯和R. Heusdens，“非平稳噪声跟踪基于数据驱动的递归噪声功率的估计”，IEEE期刊。音频，语音卷。 16，第6页。1112年至1123年，2008年8月。
见Descr iption.doc在zip文件。-Contains m-files to train and implement the noise tracking algorithm described in:
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纯C++版本的OpenTLD-v1.3.0，效果不错。-This is a C++ implementation of OpenTLD that was originally published in MATLAB by Zdenek Kalal. OpenTLD is used for tracking objects in video streams. What makes this algorithm outstanding is that it does not make use of
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Robust Non-negative Dictionary Learning for Visual Tracking
The provided codes could be either embedded into the benchmark framework of paper Online Object Tracking: A Benchmark (CVPR2013) (You can find details here: http://visual-tracking.net/) or
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可以实现视频中物体的跟踪，基本可以实现效果，但有待于改进(Object tracking in video can be achieved)
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