i am working on object tracking. i want to use background subtraction. i have tried to find out papers on background subtraction but i am really confused to use which one. I have already done tracking using just gray scale subtraction and thresholding. but now i want to model the background and then use it for tracking. i do not know much about background modelling.So, if anyone can suggest me some techniques and good papers on background subtraction and modelling, i will be greatly thankful.
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$\begingroup$ Gaussian mixture models for background modelling were once trendy. $\endgroup$– user7657Commented Jun 8, 2014 at 12:44
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$\begingroup$ Could you tell us about the papers you have read? I am interested in the subject and would welcome a primer on it. $\endgroup$– Jean-YvesCommented Jun 8, 2014 at 17:32
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$\begingroup$ You should provide some more information on the kind of images you're working with. Background subtraction is very specific to your domain. $\endgroup$– PhononCommented Jun 9, 2014 at 5:31
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$\begingroup$ OpenCV has a whole module for background subtraction that you can try with various algorithms. $\endgroup$– Adi ShavitCommented Jun 9, 2014 at 16:42
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$\begingroup$ I think that ViBe is a very good and easy to implement background modeling method. But it's patented, so be aware of that if you want to use it. $\endgroup$– MickaCommented Jun 11, 2014 at 8:55
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The seminal paper on background modeling is Adaptive background mixture models for real-time tracking by Stauffer and Grimson.
If you have Matlab and the Computer Vision System Toolbox, then you can try using vision.ForegroundDetector, which implements a version of their algorithm.