Background Subtraction Based on Nonparametric Bayesian Estimation

摘要：

Background subtraction, the task of separating foreground pixels from background pixels in a video, is an important step in video processing. Comparing with the parametric background modeling methods, nonparametric methods use a model selection criterion to choose the right number of components for each pixel online. We model the background subtraction problem with the Dirichlet process mixture, which constantly adapts both the parameters and the number of components of the mixture to the scene.

关键词： Background subtraction nonparametric methods Dirichlet process mixture

作者: Yan He Donghui Wang Miaoliang Zhu

作者单位: College of Computer Science and Technology, Zhejiang University,Hangzhou, Zhejiang, China Zhejiang F College of Computer Science and Technology, Zhejiang University,Hangzhou, Zhejiang, China

会议类型: 国际会议

会议名称: Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)

会议地点: 成都

会议语种:英文

页码: 84-88

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）