Better Foreground Segmentation for Static Cameras via New Energy Form and Dynamic Graph-cut

Authors:
Yunda Sun;Baozong Yuan;Zhenjiang Miao;Chengkai Wan
Affiliations:
Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University
Venue:
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Year:
2006

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Abstract

In this paper, we propose a new foreground segmentation method for applications using static cameras. It formulates foreground segmentation as an energy minimization problem, and produces much better results than conventional background subtraction methods. Due to the integration of better likelihood term, shadow elimination term and contrast term into energy function, it also achieves more accurate segmentation than existing method of the same type. Furthermore, real-time performance is made possible by employing dynamic graph-cut algorithm. Quantitative and qualitative experiments on real videos demonstrate our improvements.