运动目标检测的方法

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背景差分：http://docs.opencv.org/3.2.0/d1/dc5/tutorial_background_subtraction.html

vb:http://www.telecom.ulg.ac.be/research/vibe/

前景检测算法（一）--综述

前景检测的函数（Improved Background-Foreground Segmentation Methods），在2.4和3.3之间的变化。

在OpenCV 2.4里，有下面3个方法：
BackgroundSubtractorGMG()
This class implements an algorithm described in "Visual Tracking of Human Visitors under Variable-Lighting Conditions for a Responsive Audio Art Installation,"

BackgroundSubtractorMOG()
Gaussian Mixture-based Backbround/Foreground Segmentation Algorithm

BackgroundSubtractorMOG2()
"Improved adaptive Gausian mixture model for background subtraction

在opencv 3.3里，cnt()替代了mog2()：
BackgroundSubtractorCNT()
Background subtraction based on counting.
About as fast as MOG2 on a high end system. More than twice faster than MOG2 on cheap hardware

BackgroundSubtractorGMG()
This class implements an algorithm described in "Visual Tracking of Human Visitors under Variable-Lighting Conditions for a Responsive Audio Art Installation,"

BackgroundSubtractorMOG()
Gaussian Mixture-based Backbround/Foreground Segmentation Algorithm　

来源：

opencv前景检测的方法，在2.4.和3.3之间的变化

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