CAJ | 학술논문

为了有效识别视频监控领域中的打斗和抢劫等异常交互行为，提出一种基于耦合隐马尔可夫模型（CHMM）的异常交互行为识别方法。首先对人与人之间异常交互行为与正常交互行为的特征差别进行分析，然后提取了包括速度、面积变化率、目标外接矩形长宽比变化率、目标间距、目标运动方向角度差以及方向梯度直方图6类人体目标的运动特征和形态特征，并组成训练数据集，在此基础上使用耦合隐马尔可夫方法构建异常交互行为模型。实验中引入一些典型的行为数据库，如 CASIA 和 CAVIAR 数据集，通过和传统的基于隐马尔可夫模型（HMM）的识别方法进行对比，表明 CHMM 方法更适合于识别少数人的异常交互行为，且识别率更高。
위료유효식별시빈감공영역중적타두화창겁등이상교호행위，제출일충기우우합은마이가부모형（CHMM）적이상교호행위식별방법。수선대인여인지간이상교호행위여정상교호행위적특정차별진행분석，연후제취료포괄속도、면적변화솔、목표외접구형장관비변화솔、목표간거、목표운동방향각도차이급방향제도직방도6류인체목표적운동특정화형태특정，병조성훈련수거집，재차기출상사용우합은마이가부방법구건이상교호행위모형。실험중인입일사전형적행위수거고，여 CASIA 화 CAVIAR 수거집，통과화전통적기우은마이가부모형（HMM）적식별방법진행대비，표명 CHMM 방법경괄합우식별소수인적이상교호행위，차식별솔경고。
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.