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Better Foreground Segmentation for Static Cameras via New Energy Form and Dynamic Graph-cut
Hong Kong August 20-August 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.32218th International Conference on Patt ...
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Yunda Sun, Beijing Jiaotong University
Baozong Yuan, Beijing Jiaotong University
Zhenjiang Miao, Beijing Jiaotong University
Chengkai Wan, Beijing Jiaotong University
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.
Citation:
Yunda Sun, Baozong Yuan, Zhenjiang Miao, Chengkai Wan, "Better Foreground Segmentation for Static Cameras via New Energy Form and Dynamic Graph-cut," icpr, vol. 4, pp.49-52, 18th International Conference on Pattern Recognition (ICPR'06) Volume 4, 2006
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