【学习】使用OpenCV的目标跟踪技术(C ++ / Python)

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摘要

 

转自:视觉机器人

在本教程中,我们将了解OpenCV 3.0中引入的OpenCV跟踪API。 我们将学习如何以及何时使用OpenCV 3.2 - BOOSTING, MIL, KCF,TLD,MEDIANFLOW和GOTURN中提供的6种不同的跟踪器。 我们还将学习现代跟踪算法背后的一般理论。


In this tutorial, we will learn about OpenCV tracking API that was introduced in OpenCV 3.0.  We will learn how and when to use the 6 different trackers available in OpenCV 3.2 — BOOSTING, MIL, KCF, TLD, MEDIANFLOW, and GOTURN. We will also learn the general theory behind modern tracking algorithms.

This problem has been perfectly solved by my friend Boris Babenko as shown in this flawless real-time face tracker below! Jokes aside, the animation demonstrates what we want from an ideal object tracker — speed, accuracy, and robustness to occlusion.


链接:

Object Tracking using OpenCV (C++/Python)


原文链接:

http://weibo.com/5501429448/Evucdcljt?from=page_1005055501429448_profile&wvr=6&mod=weibotime&type=comment#_rnd1487147919242

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