【学习】使用OpenCV的目标跟踪技术（C ++ / Python）
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：
原文链接：
http://weibo.com/5501429448/Evucdcljt?from=page_1005055501429448_profile&wvr=6&mod=weibotime&type=comment#_rnd1487147919242
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