标题:Transductive Segmentation of Live Video with Non-stationary Background
作者:Zhong, Fan; Qin, Xueying; Peng, Qunsheng
通讯作者:Peng, Q
作者机构:[Zhong, Fan; Peng, Qunsheng] Zhejiang Univ, State Key Lab CAD&CG, Hangzhou, Zhejiang, Peoples R China.; [Qin, Xueying] Shandong Univ, Dept Comp Sci, 更多
会议名称:23rd IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
会议日期:JUN 13-18, 2010
来源:2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR)
出版年:2010
页码:2189-2196
DOI:10.1109/CVPR.2010.5539899
摘要:Online foreground extraction is very difficult due to the complexity of real scenes. Almost all the previous methods assume that the background is stationary, which not only incur unreliable result due to background activities like dynamic shadow, moving background objects etc., but also makes them hard to be extended to the case of non-stationary background.; In this paper we assume that the background is continuous instead of stationary, and present a transductive video segmentation method that can handle dynamic scenes captured by a hand-held moving camera. The segmentation is propagated based on local color models and temporal prior, as well as a dynamic global color model (DGKDE) in the case of occlusion. A novel local color modeling method, FLKDE, is proposed to model both local color distribution and temporal prior at each pixel. FLKDE can be learned additively to reach real-time speed. Finally, a very fast geodesic-based method is adopted to solve for the segmentation. Experiments show that our method can generate good quality segmentation for wide variety of scenes, and can reach 15 similar to 25 fps for 640x480 size of input image sequences.
收录类别:CPCI-S;EI;SCOPUS
WOS核心被引频次:7
Scopus被引频次:14
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-77955994041&doi=10.1109%2fCVPR.2010.5539899&partnerID=40&md5=7139a99272b75175c4ecda16247f08c3
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