东南大学学报（自然科学版）Issue(6)：1217-1221,5.DOI:10.3969/j.issn.1001-0505.2013.06.016
基于耦合隐马尔可夫模型的异常交互行为识别
Recognition of abnormal interactions based on coupled hidden Markov models
摘要
Abstract
To effectively recognize the abnormal interactions such as fighting and robbing in an intel-ligent video surveillance area,a recognition method for abnormal interactions based on coupled hid-den Markov models (CHMM)is presented.First,the difference between the features of abnormal interactions and that of normal interactions is analyzed.Then the motion features and shape features of the object are extracted to construct the training data set,which are the speed,area change rate, change rate of the bounding rectangle aspect ratio,distance,angle difference of motion direction and the histogram of oriented gradients.Based on them,the CHMM is exploited to construct the abnor-mal interactions model.In the experiments,some classical test cases such as CASIA and CAVIAR are used,and the traditional recognition based on hidden Markov models (HMM)is adopted for comparison.By these experiments,it is proved that the CHMM is more suitable for recognizing the abnormal interactions between fewer people than the HMM,and the recognition rate of the CHMM is higher than that of the HMM.关键词
异常交互行为/耦合隐马尔可夫模型/运动特征/形态特征Key words
abnormal interactions/coupled hidden Markov models/motion feature/shape feature分类
信息技术与安全科学引用本文复制引用
林国余,柏云,张为公..基于耦合隐马尔可夫模型的异常交互行为识别[J].东南大学学报（自然科学版）,2013,(6):1217-1221,5.基金项目
国家自然科学基金资助项目（60972001）、苏州市科技计划资助项目（SG201076）． （）
