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Background modeling is a technique for extracting moving objects in video frames. This technique can be used in ma-chine vision applications, such as video frame compression and monitoring. To model the background in video frames, initially, a model of scene background is constructed, then the current frame is subtracted from the background. Even-tually, the difference determines the moving objects. This paper evaluates a number of existing background modeling techniques in term of accuracy, speed and memory requirement.
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Hassanpour et al. (2011) studied this question.
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