%0 Journal Article
%T Bayesian Human Recognition Across Multiple Cameras in Crowded Situations<br>基于贝叶斯模型的相机间人群目标识别
%A DENG Ying-n
%A ZHU Hong
%A LIU Wei
%A <br>邓颖娜
%A 朱虹
%A 刘薇
%J 中国图象图形学报
%D 2009
%I 
%X Getting exact human position under occlusion is a key problem to object recognition across multiple cameras with overlapped views.The problem of human segmentation was converted to maximize the posteriori estimation by constructing a human model and a Bayesian model. And then the same objects were matched in different views on the least distance principal by taking the human axis as a feature. Experiments show promising results on human segmentation and recognition in crowded situations and the accuracy rate is high.
%K Bayesian model
%K object recognition
%K crowd segmentation
%K human model<br>贝叶斯模型
%K 目标识别
%K 人群分割
%K 人体模型
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=00299EE446645543D5D828F15419F151&yid=DE12191FBD62783C&vid=F3583C8E78166B9E&iid=9CF7A0430CBB2DFD&sid=5AD409C6B641DD28&eid=290C357E8EC0A94B&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=11