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| Foreground Object Detection in Complex Background Based on Bayes-total Probability Joint Estimation |
| Li Yong-jun① Zeng Biao② Xu Ke-fu③ Li Yang③ |
①(School of Computer Science and engineering, South China University of Technology, Guangzhou 510006, China)
②(School of Sciences, South China University of Technology, Guangzhou 510640, China)
③(Institute of Computing Technology, Chinese Academy of Sciences, |
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Abstract For the difficulty or low accuracy on foreground extraction in a complex environment, this paper proposes Bayes-total probability joint estimation for the detection and segmentation of foreground objects and the definition of background error control variable. Under the criterion of Bayes-total probability joint estimation, background pixels will be divided into stationary and moving types by choosing a proper feature vector, and foreground pixels can be detected accurately. Experiment results show the proposed method is a more general model for target detection, and it is also promising in extracting foreground objects under different kinds of background from video (containing complex background).
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Received: 26 June 2011
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Corresponding Authors:
Li Yong-jun
E-mail: liyj@scut.edu.cn
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2012, Vol. 34 
