%0 Journal Article
%T A Method of Abnormal Action Recognition in Variable Scenarios<br>可变场所的异常行为识别方法
%A ZHANG Jun
%A LIU Zhi-jing
%A <br>张军
%A 刘志镜
%J 中国图象图形学报
%D 2009
%I 
%X Different understanding results in different scenarios even for the same person to conduet visual analysis. In order to determine whether the behavior is abnormal in different scenarios, a double-layer bag-of-words model is proposed to solve the problem in surveillance system. The video information is processed in the first layer of Bag-of-Words, and the information of scenario-action text words is included in the second one. A video sequence is represented as a collection of spatial-temporal codebook by extracting space-time interest points. A behavior characteristic is represented as a collection of behavior text words in special scenarios. Probabilistic latent semantic analysis(pLSA)model is adopted to automatically learn the probability distributions of spatial-temporal words and the topics correspond to human action categories. PLSA also can learn the probability distributions of the motion text words in a scenario with supervisor and the topics correspond to anomalous or normal actions. The algorithm can categorize the human anomalous or normal action contained in the special occasion to a novel video sequence after being trained.
%K abnormal action
%K interest points
%K double-layer bag-of-words
%K probabilistic latent semantic analysis
%K variable scenarios<br>异常行为
%K 兴趣点
%K 双层词包
%K 潜在含语义分析概率
%K 可变场所
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=9F4ACAAE7F1EABDA89B5FD8EFD42CDFF&yid=DE12191FBD62783C&vid=F3583C8E78166B9E&iid=F3090AE9B60B7ED1&sid=D1DBBF7482A512F1&eid=1F552201CAFF2426&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=7