机构

• 计算技术研究所 [2]
• 长春光学精密机械与物... [1]
• 自动化研究所 [1]
• 西安光学精密机械研究... [1]

采集方式

• OAI收割 [5]

内容类型

• 期刊论文 [4]
• 会议论文 [1]

发表日期

• 2019 [1]
• 2017 [2]
• 2014 [1]
• 2011 [1]

学科主题

筛选

浏览/检索结果: 共5条，第1-5条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 Effective Crowd Anomaly Detection Through Spatio-temporal Texture Analysis 期刊论文  OAI收割 International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 1, 页码: 27-39 作者:  Yu Hao;  Zhi-Jie Xu;  Ying Liu;  Jing Wang;  Jiu-Lun Fan   |  收藏  |  浏览/下载：36/0  |  提交时间：2021/02/22 Crowd behavior  spatial-temporal texture  gray level co-occurrence matrix  information entropy.   Patch-based topic model for group detection 期刊论文  OAI收割 SCIENCE CHINA-INFORMATION SCIENCES, 2017, 卷号: 60, 期号: 11 作者:  Chen, Mulin;  Wang, Qi;  Li, Xuelong   |  收藏  |  浏览/下载：28/0  |  提交时间：2017/12/26 Group Detection  Collective Behavior  Crowd Analysis  Latent Topic   Exploring Coherent Motion Patterns via Structured Trajectory Learning for Crowd Mood Modeling 期刊论文  OAI收割 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2017, 卷号: 27, 期号: 3, 页码: 635-648 作者:  Zhang, Yanhao;  Qin, Lei;  Ji, Rongrong;  Zhao, Sicheng;  Huang, Qingming   |  收藏  |  浏览/下载：32/0  |  提交时间：2019/12/12 Coherent motion pattern  crowd behavior analysis  emotional motion feature  structured trajectory learning (STL)   Crowd Simulation and Its Applications: Recent Advances 期刊论文  OAI收割 JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2014, 卷号: 29, 期号: 5, 页码: 799 作者:  Xu MingLiang;  Jiang Hao;  Jin XiaoGang;  Deng Zhigang   |  收藏  |  浏览/下载：5/0  |  提交时间：2023/12/04 SOCIAL FORCE MODEL  PEDESTRIAN BEHAVIOR  TRAFFIC SIMULATION  NAVIGATION  ANIMATION  ENVIRONMENTS  EVACUATION  FLOW  FIELDS  crowd simulation  emergency evacuation  pedestrian crowd  crowd formation  traffic simulation  swarm simulation   Approach for detecting crowd panic behavior based on fluid kinematic features and entropy (EI CONFERENCE) 会议论文  OAI收割 International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2011, November 19, 2011 - November 23, 2011, Suzhou, China 作者:  Li Y.;  Li Y.;  Li Y.;  Zhang X.;  Zhang X. 收藏  |  浏览/下载：30/0  |  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.