如何提高斑点检测精度？
考虑下面的图片：这是几个人互相交谈的视频中的一个帧。我尝试对该视频进行斑点检测，但是当两个人彼此靠近时，它被视为一个斑点。 有没有办法改进斑点检测，以便我可以更有效地检测人员？！[斑点][1]
Consider the following picture: it is a frame from a video of few people talking to each other. I have tried to do blob detection on that video, but when two persons are near each other, it is considered as one blob.
Is there a way to improve the blob detection, so that I can detect people more efficiently?![Blobs][1]
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这个问题称为
遮挡。这是一个典型的问题，您需要卡尔曼滤波器的帮助。
卡尔曼滤波器采用先前的值并预测未来的值。它在嘈杂的情况或不准确的情况下非常有用。
SO里有很多讨论，简单搜索一下就可以找到。但我发现其中两个非常有用
1) 有关跟踪的问题使用卡尔曼滤波器移动球
2) 使用卡尔曼滤波器来跟踪物体的位置，但需要知道该物体的位置作为卡尔曼滤波器的输入。发生了什么事？
和卡尔曼滤波器已经在 OpenCV 中实现并且内置函数可用。
还要在多个 Blob 跟踪上检查此 SO：多个 Blob 跟踪
这不仅仅是方法。你可以在谷歌上找到很多关于这方面的论文。
<强><一href="https://docs.google.com/viewer?a=v&q=cache:r-h912e0B4gJ:cvrc.ece.utexas.edu/Publications/tracking_multiple_body_parts.pdf%20how%20to%20track%20multiple%20blobs& ;hl=en&gl=in&pid =bl&srcid=ADGEESji6NjTEqlHfJr9B578AKSeh9hssxPUqFylmM5bAxPSRzItSsLzGPd2eXPGlXtGFK7LXrrFE74E4TyvC xYDuPODD1mdneJooJqpP6EfWt2dzkeuLFRtkymC0e8g417nWZCdFFYg&sig=AHIEtbR0AcUrz7cG2gZpdKTffXBCP6PpnQ" rel="nofollow noreferrer">论文1：这篇论文解释了另一种方法。可能有用。
此处可以找到大量专门讨论该主题的论文。
This problem is called
Occlusion.This is a typical problem where you need help of
Kalman Filter.Kalman filter takes previous values and predicts the future values. It is highly useful in noisy situations or inaccurate situations.
A lot of discussions are there in SO, which you can find by simple searching. But i found two of them really useful
1) Question on tracking a moving ball using Kalman filter
2) Use Kalman filter to track the position of an object, but need to know the position of that object as an input of Kalman filter. What is going on?
And Kalman filter is already implemented in OpenCV and inbuilt functions are available.
Also check this SO on multiple blob tracking : Multiple Blob Tracking
This is not only method. You can find plenty of papers regarding this on googling.
Paper 1 : This paper explains another method. Might be useful.
A lots of papers exclusively on this subject can be found here.