Institute of Computing Technology, Chinese Academy IR
Exploring Coherent Motion Patterns via Structured Trajectory Learning for Crowd Mood Modeling | |
Zhang, Yanhao1; Qin, Lei2; Ji, Rongrong3; Zhao, Sicheng1; Huang, Qingming1,4; Luo, Jiebo5 | |
2017-03-01 | |
发表期刊 | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY |
ISSN | 1051-8215 |
卷号 | 27期号:3页码:635-648 |
摘要 | Crowd behavior analysis has recently attracted extensive attention in research. However, the existing research mainly focuses on investigating motion patterns in crowds, while the emotional aspects of crowd behaviors are left unexplored. Analyzing the emotion of crowd behaviors is indeed extremely important, as it uncovers the social moods that are beneficial for video surveillance. In this paper, we propose a novel crowd representation termed crowd mood. Crowd mood is established based upon the discovery that the social emotional hypothesis of crowd behaviors can be revealed by investigating the spacing interactions and the structural levels of motion patterns in crowds. To this end, we first learn the structured trajectories of crowds by particle advection using low-rank approximation with group sparsity constraint, which implicitly characterizes the coherent motion patterns. Second, rich emotional motion features are explicitly extracted and fused by support vector regression to reflect social characteristics. In particular, we construct weighted features in a boosted manner by considering the features' significance. Finally, crowd mood is intuitively presented as affective curves to track the emotion states of the crowd dynamics, which is robust to noise, sensitive to semantic shift, and compact for pattern expressions. Extensive evaluations on crowd video data sets demonstrate that our approach effectively models crowd mood and achieves significantly better results with comparisons to several alternative and state-of-the-art approaches for various tasks, i. e., crowd mood classification, global abnormal mood detection, and crowd emotion matching. |
关键词 | Coherent motion pattern crowd behavior analysis emotional motion feature structured trajectory learning (STL) |
DOI | 10.1109/TCSVT.2016.2593609 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Basic Research Program of China (973 Program)[2015CB351802] ; National Basic Research Program of China (973 Program)[2012CB316400] ; National Natural Science Foundation of China[61402388] ; National Natural Science Foundation of China[61332016] ; National Natural Science Foundation of China[61133003] ; National Natural Science Foundation of China[61390510] ; National Natural Science Foundation of China[61572465] |
WOS研究方向 | Engineering |
WOS类目 | Engineering, Electrical & Electronic |
WOS记录号 | WOS:000397576200020 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/7351 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Qin, Lei |
作者单位 | 1.Harbin Inst Technol, Sch Comp Sci, Harbin 150001, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 3.Xiamen Univ, Dept Cognit Sci, Sch Informat Sci & Engn, Xiamen 361005, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100190, Peoples R China 5.Univ Rochester, Dept Comp Sci, Rochester, NY 14627 USA |
推荐引用方式 GB/T 7714 | Zhang, Yanhao,Qin, Lei,Ji, Rongrong,et al. Exploring Coherent Motion Patterns via Structured Trajectory Learning for Crowd Mood Modeling[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2017,27(3):635-648. |
APA | Zhang, Yanhao,Qin, Lei,Ji, Rongrong,Zhao, Sicheng,Huang, Qingming,&Luo, Jiebo.(2017).Exploring Coherent Motion Patterns via Structured Trajectory Learning for Crowd Mood Modeling.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,27(3),635-648. |
MLA | Zhang, Yanhao,et al."Exploring Coherent Motion Patterns via Structured Trajectory Learning for Crowd Mood Modeling".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 27.3(2017):635-648. |
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