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S.-T. Su and Y.-Y. Chen, “Moving Object Segmentation Using Improved Running Gaussian Average Background Model,” Digital Image Computing: Techniques and Applications, 2006, pp. 24-30.

has been cited by the following article:

• TITLE: Video Frame’s Background Modeling: Reviewing the Techniques

  AUTHORS: Hamid Hassanpour, Mehdi Sedighi, Ali Reza Manashty

  KEYWORDS: Background Modeling, Moving Object

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.2 No.2, May 26, 2011

  ABSTRACT: 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.