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Moving Objects Detection and Segmentation Based on Background Subtraction and Image Over-Segmentation

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Executive Summary

Moving objects detection is a fundamental step in many vision based applications. Background subtraction is the typical method. Many background models have been introduced to deal with different problems. The method based on mixture of Gaussians is a good balance between accuracy and complexity, and is used frequently by many researchers. But it still cannot provide satisfied results in some cases. In this paper, the authors solve this problem by introducing a post process to the initial results of mixture of Gaussians method. An over-segmentation based on color information is used to segment the input frame into patches.

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