摘要
人体动作行为识别因其在视频监控、虚拟现实、人机智能交互等领域的广泛应用而成为计算机视觉领域的研究热点.文中将人体动作行为识别问题归纳为计算机经过检测动作数据而获取并符号化动作信息,继而提取和理解动作特征以实现动作行为分类的过程,在此基础上,从运动目标检测、动作特征提取和动作特征理解3个方面对涉及到的技术进行回顾分析,对相关方法进行分类,并讨论相关难点和研究方向.
Action recognition has become a hotspot in the fields of video surveillance, virtual reality, human- computer interaction and others recently. In this paper, action recognition is comprehended as a process of detecting action data, called symbols of action message, and distinct actions based on action feature extraction and reception are further classified. On the basis, an overview of vision-based full-body action recognition techniques is presented within the domain of moving object detection, action feature extraction and action feature perception, and the corresponding methods are classified. Besides, the research trend of action recognition is discussed.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2014年第1期35-48,共14页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金项目(No.61273336)
国家教育部博士点专项基金项目(No.20122302120039)
中央高校基本科研业务费专项资金项目(No.HIT.NSRIF.201172)资助
关键词
动作识别
运动目标检测
动作特征提取
动作特征理解
Action Recognition, Moving Object Detection , Action Feature Extraction, Action FeaturePerception
