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基于光流的人体行为识别 被引量:1

Action Recognition Based on the Optical Flow
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摘要 人体行为识别已成为计算机视觉中的一个研究热点,并且光流法已被应用到各种应用场合。针对教室内学生的站立和坐下的视频,提出了基于光流的人体行为识别算法。首先获取当前帧的活动点集,从而得到活动区域。根据保存帧的信息统计向上光流和向下光流,结合当前人的状态,判断出人的动作。最后进行人的状态的更新。在整个视频处理过程中,该算法重复以上过程,维持了站立人的状态跟踪。实验结果表明,该算法能够识别出站立和坐下的动作,验证了该算法的有效性和鲁棒性。 Recognition of human action has become a hot research topic in computer vision,and optical flow method has been applied to a variety of applications.The action recognition based on optical flow is provided for the video of student standing up and sitting down in the classroom.First,the active area is maintained through the active point set of the current frame.According to the statistical information of optical flows of the saved frames,the upward and downward optical flows are calculated.The hu man action is determined combining the current state of the human.Finally,the state is updated.Throughout the video process ing,the algorithm above process is repeated,maintaining the status tracking of the standing person.Experimental results show that the algorithm is able to identify the action of standing up and sitting down,which verifies the effectiveness and robustness of the algorithm.
作者 鲁统伟 任莹 LU Tong-wei,REN Ying(School of Computer Science and Engineering,Wuhan Institute of Technology,Wuhan,430074,China)
出处 《电脑知识与技术》 2013年第3期1610-1612,共3页 Computer Knowledge and Technology
关键词 光流 人体行为识别 跟踪 活动区域 视频处理 optical flow action recognition tracking active area video processing
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  • 1阮涛涛,姚明海,瞿心昱,楼中望.基于视觉的人体运动分析综述[J].计算机系统应用,2011,20(2):245-254. 被引量:26
  • 2Turaga P, Chellappa R, Subrahmanian V S, et al. Machine recognition of human activities: A survey. IEEE Trans. Circuits Syst. VideoTechnol. 2008,18,(11): 1473-1488.
  • 3Rapantzikos,K., Avrithis, Y.,and Kollias, S. Dense saliency-based spatiotemporal feature points for action recognition[C]. In Proceedingsof the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, Los Alamitos, CA, 2009: 1454-1461.
  • 4Rapantzikos,K., Avrithis, Y.,and Kollias, S. Dense saliency-based spatiotemporal feature points for action recognition[C]. In Proceedingsof the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, Los Alamitos, CA, 2009: 1454-1461.
  • 5Dai, P., Di, H., Dong, L., Tao, L., and Xu, G. Group interaction analysis in dynamic context[J]. IEEE Trans. Syst. Man Cybem. Part B.2008,38( 1): 275—282.
  • 6赵海勇,刘志镜,张浩.基于模板匹配的人体日常行为识别[J].湖南大学学报(自然科学版),2011,38(2):88-92. 被引量:11
  • 7李宁,须德,傅晓英,袁玲.结合人体运动特征的行为识别[J].北京交通大学学报,2009,33(2):6-10. 被引量:15
  • 8钱堃,马旭东,戴先中.基于抽象隐马尔可夫模型的运动行为识别方法[J].模式识别与人工智能,2009,22(3):433-439. 被引量:17
  • 9韩磊,李君峰,贾云得.基于时空单词的两人交互行为识别方法[J].计算机学报,2010,33(4):776-784. 被引量:25
  • 10Baker S,Scharstein D, Lewis J,et al. A database and evaluation methodology for optical flow[C]. In Proceedings of the IEEE internationalconference on computer vision. Rio de Janeiro .2007: 1-8.

二级参考文献138

  • 1刘相滨,向坚持,王胜春.人行为识别与理解研究探讨[J].计算机与现代化,2004(12):1-5. 被引量:12
  • 2李妍婷,罗予频,唐光荣.单目视频中的多视角行为识别方法[J].计算机应用,2006,26(7):1592-1594. 被引量:8
  • 3杜友田,陈峰,徐文立,李永彬.基于视觉的人的运动识别综述[J].电子学报,2007,35(1):84-90. 被引量:79
  • 4Xuedong Huang, Alex Acero, Hsiao-wuen Hon. Spoken Language Processing-A Guide to Theory Algorithms and System Development [ M ]. New Jersey: Prentice Hall Books, 2001:375 - 411.
  • 5Marco Leo, Tiziana D'Orazio, Paolo Spagnolo. Human Activity Recognition for Automatic Visual Surveillance of Wide Areas[ C ]//Proc. of the 2nd Inter. Workshop on Video Surveillance and Sensor Networks ACM, 2004:124 - 130.
  • 6Chen Hsuansheng, Chen Huatsung, Chen Yiwen, et al. Human Action Recognition Using Star Skeleton [ C]// Proc. of the 4th Inter. Workshop on Video Surveillance and Sensor Networks ACM, 2006:171 - 178.
  • 7Li X. HMM Based Action Recognition Using Oriented Histograms of Optical Flow Field[ J]. Electronics Letters IET, 2007,43 (10) : 560 - 561.
  • 8Ahmad M, Seong-Whan Lee. HMM-Based Human Action Recognition Using Muhiview Image Sequences[C] ff The 18th Inter. Conf. on Pattern Recognition, 2006, 1:263 - 266.
  • 9Schindler K, Van Gool L. Action Snippets: How Many Frames Does Human Action Recognition Require? [C]// IEEE CVPR, 2008:1-8.
  • 10Stauffer C, Grimson W E L. Adaptive Background Mixturemodels for Real-Time Tracking[C]// IEEE Computer Society Conf. on CVPR, 1999,2:23- 25.

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