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北京大学 [1]

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	面向智能监控的人类异常行为检测方法研究学位论文博士, 沈阳: 中国科学院沈阳自动化研究所, 2018 作者: 周培培; 杨亮收藏 \| 浏览/下载：56/0 \| 提交时间：2018/06/16 计算机视觉视频分析人群异常检测暴力异常检测人数异常检测
	Action Extraction in Continuous Unconstrained Video for Cloud-Based Intelligent Service Robot 期刊论文 IEEE access, 2018 作者: Huiwen Guo; Xinyu Wu; Nannan Li 收藏 \| 浏览/下载：26/0 \| 提交时间：2019/01/31
	Crowd motion segmentation and behavior recognition fusing streak flow and collectiveness 期刊论文 OPTICAL ENGINEERING, 2018, 卷号: 57, 期号: 4 作者: Gao, Mingliang; Jiang, Jun; Shen, Jin; Zou, Guofeng; Fu, Guixia 收藏 \| 浏览/下载：6/0 \| 提交时间：2019/12/11 crowd motion segmentation crowd behavior recognition collective motion streak flow collectiveness
	Real-time and generic queue time estimation based on mobile crowdsensing 期刊论文 FRONTIERS OF COMPUTER SCIENCE, 2017 Wang, Jiangtao; Wang, Yasha; Zhang, Daqing; Wang, Leye; Chen, Chao; Lee, Jae Woong; He, Yuanduo 收藏 \| 浏览/下载：5/0 \| 提交时间：2017/12/03 mobile crowdsensing queue time estimation opportunistic and participatory sensing PEOPLE RECOGNITION SCENES
	Exemplar-AMMs: Recognizing Crowd Movements From Pedestrian Trajectories 期刊论文 IEEE TRANSACTIONS ON MULTIMEDIA, 2016, 卷号: 18, 页码: 2398-2406 作者: Liu, Wenxi; Lau, Rynson W. H.; Wang, Xiaogang; Manocha, Dinesh 收藏 \| 浏览/下载：3/0 \| 提交时间：2019/11/21 crowd simulation Crowd behavior modeling pattern recognition video surveillance
	Online Anomaly Detection in Crowd Scenes via Structure Analysis 期刊论文 ieee transactions on cybernetics, 2015, 卷号: 45, 期号: 3, 页码: 562-575 作者: Yuan, Yuan; Fang, Jianwu; Wang, Qi 收藏 \| 浏览/下载：25/0 \| 提交时间：2015/07/15 Anomaly detection computer vision machine learning object tracking structure analysis video analysis
	Understanding collective crowd behaviors: Learning a Mixture model of Dynamic pedestrian-Agents 会议论文 Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012., 美国作者: Bolei Zhou; Xiaogang Wang; Xiaoou Tang 收藏 \| 浏览/下载：8/0 \| 提交时间：2015/08/25
	Approach for detecting crowd panic behavior based on fluid kinematic features and entropy (EI CONFERENCE) 会议论文 International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2011, November 19, 2011 - November 23, 2011, Suzhou, China Cao S.; Zhang X.; Cao W.; Liu C.; Li Y.; Li P. C. 收藏 \| 浏览/下载：21/0 \| 提交时间：2013/03/25 Crowd panic behavior detection is an important task in video analysis and event recognition whose purpose is to detect when the panic behavior happened and alarming the abnormal event timely. In this paper the crowd is regard as a fluid and the crowd motion is described by four fluid kinematic features (divergence vorticity gradient tensor invariant and rotation tensor invariant). To discriminate the panic event from normal crowd behavior an information entropy is calculated as a high level feature based on the fluid kinematic features. Experimental results show that the entropy raised dramatically once a panic event happened.

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