CASIA OpenIR  > 智能制造技术与系统研究中心  > 多维数据分析
A new motion detection algorithm based on snake and mean shift
Liu Yulan; Peng Silong; Yulan Liu
2008
Conference Name1st International Congress on Image and Signal Processing CISP 2008
Pagespp 140-144
Conference Date2008/5/27-2008/5/30
Conference Place中国Sanya Hainan China
AbstractActive contour model and mean shift are both motion detection algorithms. Each of them has its own merits and shortcomings. An active contour tends to be tracked by noise points and results in a false boundary. A mean shift vector always points to the edge area when the start point is around the object With initial curves given near the objects in each image automatically we presented a new motion detection algorithm which used the internal energy of active contour to keep a curve continuous and smooth and also used the mean shift vector to track the curve to the real object boundary step by step with an iterative process. Experimental results showed that this algorithm can improve the segmenting results greatly in noisy videos.
KeywordMotion Diction Active Contour Model Mean Shift Video Surveillance
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12885
Collection智能制造技术与系统研究中心_多维数据分析
Corresponding AuthorYulan Liu
Recommended Citation
GB/T 7714
Liu Yulan,Peng Silong,Yulan Liu. A new motion detection algorithm based on snake and mean shift[C],2008:pp 140-144.
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