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| Bilayer Video Segmentation Based on Random Ferns |
| CHU Yi-Ping1, CHEN Qin1, HUANG Ye-Jue2, ZHENG He-Rong3 |
1.College of Computer Science, Hangzhou Dianzi University, Hangzhou 310018
2.School of Computer, Zhejiang Industry Polytechnic College, Shaoxing 312000
3.College of Software, Zhejiang University of Technology, Hangzhou 310027 |
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Abstract A random ferns based method is proposed for bilayer video segmentation with the capability of segmenting monocular video automatically. Motion feature dictionary is constructed by clustering the motion features of the video, and the motion features are modeled by random ferns. The video colors, motion features and neighboring relationships are constrained by using conditional random fields. The graph-cut algorithm is adopted for solving globally optimal segmentation results. The experimental results demonstrate the validity of the proposed algorithm, and the results of the proposed method are compared with other algorithms on different video data.
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Received: 04 September 2008
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2009, Vol. 22 
