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Occlusion Boundary Detection by Combining Appearance, Motion and Edge Structure Cues in Video |
ZHANG Shi-hui1,2,ZHANG Hong-qiao1,HAN De-wei1 |
1. School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei 066004,China
2. The Key Lab for Computer Virtual Tech & Sys Integration of Hebei Province, Qinhuangdao, Hebei 066004,China |
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Abstract To detect the occlusion boundary in video sequences accurately, an occlusion boundary detection approach based on random forests classifier is proposed. Firstly, the edges of current frame in a video are segmented to obtain superpixels and superpixel edges, and then the superpixels edges are decomposed into short line fragments. Secondly, the occlusion related features of each line fragment are extracted by combining appearance, motion and edge structure cues and the extracted features are assembled to feature vector. After that, the feature vector of each line fragment is inputted to the occlusion boundary classifier to detect whether each line fragment is an occlusion boundary or not. Finally, the occlusion boundary of the current frame in a video is obtained by visualizing all the line fragments which belong to occlusion boundary. The experimental results show that the proposed approach has higher accuracy.
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Received: 30 June 2014
Published: 22 March 2016
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Corresponding Authors:
Shi-hui ZHANG
E-mail: sshhzz@ysu.edu.cn
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