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	A new video object segmentation algorithm by fusion of spatio-temporal information based on GMM learning
	Zhu qingsong; Xie yaoqin; Gu jia; Wang lei
	2011
会议名称	2011 International Conference on Automation and Robotics, ICAR 2011
会议地点	Shanghai
英文摘要	In the field of surveillance, Effective and rapid video object segmentation is a key technology for video analysis and processing. For the complex scene and noise that affect segmentation issue in the fixed occasion, on the base of classic Gaussian Mixture Background Model (GMM), a new algorithm named the fusion of Spatio-Temporal based on GMM is proposed for video object segmentation, which classifies for each pixel in Time and Space scales. Firstly, the algorithm constructs dynamically Gaussian Mixture Background Model for each pixel and segment foreground objects through background subtraction. Secondly, the algorithm detects synchronously the neighborhood statistic feature of each pixel through two lemmas. Finally, a result is produced using the spatial segmentation coupling with the temporal segmentation by "and" operator. Experiments show that our proposed algorithm can segment the moving object effectively and quickly from videosequences and has stronger robustness application prospect contrasted with other algorithms. © 2011 Springer-Verlag.(16 refs)
收录类别	EI
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/3542]
专题	深圳先进技术研究院_医工所
作者单位	2011
推荐引用方式 GB/T 7714	Zhu qingsong,Xie yaoqin,Gu jia,et al. A new video object segmentation algorithm by fusion of spatio-temporal information based on GMM learning[C]. 见:2011 International Conference on Automation and Robotics, ICAR 2011. Shanghai.

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