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Proceedings Paper

An efficient approach of moving objects detection in complex background
Author(s): Min Liu; Weizhong Liu; Daoli Zhang
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Paper Abstract

Detecting moving objects is the first step of many video surveillance applications. Most existing simple background subtraction methods such as frame difference, running average (RA), and median filter, have the low computational cost, but they can't perform well in the complex scenes. Although some ordinary methods can do well in the complex scenes, they can't satisfy the real-time requirement because of its high computational cost. So in this paper, we propose an efficient approach for detecting moving objects, which has the low computational cost and high performance in the complex scenes. The proposed method first uses the running average algorithm and contour information to obtain moving regions roughly. Then an improved GMM algorithm is used to update the background model and detect foreground precisely. The experiment results show that our method has a lower computational cost and performs better both in the outdoor and indoor scenes than GMM.

Paper Details

Date Published: 30 October 2009
PDF: 5 pages
Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74952V (30 October 2009); doi: 10.1117/12.831343
Show Author Affiliations
Min Liu, Huazhong Univ. of Science and Technology (China)
Weizhong Liu, Huazhong Univ. of Science and Technology (China)
Daoli Zhang, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 7495:
MIPPR 2009: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Bruce Hirsch; Zhiguo Cao; Hanqing Lu, Editor(s)

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