摘要
行人异常行为的自动检测与识别是计算机视觉领域的重点和难点,同时也是智能监控系统中研究的热点问题。针对这一问题,提出了一种基于人体形态特征的异常检测算法。利用轮廓信息将目标从视频序列中分割出来,再对分割出来的目标进行轮廓拟合,根据所得到的拟合信息提取文中所定义的形态特征因子,将特征因子经过行为分类器的判定,从而决策出该行为是否异常。实验结果表明该方法实现简单,具有较好的实时性与鲁棒性,可以作为实时监控系统中异常行为检测的有效方法。
Automatic recognition of human behavior is an important but difficult problem in the area of computer vision.In this paper,a novel approach is introduced to handle the problem.Human body is detected using the contour information and the posture features are extracted by the contour fitting.A behavior classifier based on the normal behavior template is established to determine whether a human behavior is normal or not.Experimental results show that this system can run in real-time for the detection of abnormal behaviors with limited information and produce robust results by making full use of posture features information.
出处
《计算机工程与应用》
CSCD
2012年第3期192-194,220,共4页
Computer Engineering and Applications
关键词
异常检测
形态特征
运动分割
视频监控
anomaly detection
posture feature
motion segmentation
video surveillance
