%0 Journal Article
%T Foreground detection based on unsupervised background clustering<br>利用背景聚类的快速前景分割算法
%A Jiang peng
%A Qin Xiaolin
%A <br>蒋鹏
%A 秦小麟
%J 中国图象图形学报
%D 2010
%I 
%X A statistical background subtraction technique is proposed based on clustering of temporal color/intensity. An un-supervised clustering method is proposed to model a background with serial of clusters. The unimodal or multimodal distributions of background are detected adaptively. We use a Gaussians model to simulate each cluster which prevents the estimation the parameter of mix of Gaussians model. The foreground will be detected by comparing the background possibility with a threshold. Experimental results show our approach has equal or better segmentation performance and is proved capable of real-time processing.
%K unsupervised clustering
%K Gaussians model
%K adaptive<br>无监督聚类
%K 高斯模型
%K 自适应
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=25EE3F9316E667C3ED4BE6B28260E1FE&yid=140ECF96957D60B2&vid=23CCDDCD68FFCC2F&iid=59906B3B2830C2C5&sid=D227C2A170C3A3E4&eid=82D2CD7E370B154A&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=0