Patch-based topic model for group detection | |
Chen, Mulin1,2; Wang, Qi1,2,3; Li, Xuelong4 | |
刊名 | SCIENCE CHINA-INFORMATION SCIENCES |
2017-11-01 | |
卷号 | 60期号:11 |
关键词 | Group Detection Collective Behavior Crowd Analysis Latent Topic |
ISSN号 | 1674-733X |
DOI | 10.1007/s11432-017-9237-1 |
产权排序 | 4 |
文献子类 | Article |
英文摘要 | Pedestrians in crowd scenes tend to connect with each other and form coherent groups. In order to investigate the collective behaviors in crowds, plenty of studies have been conducted on group detection. However, most of the existing methods are limited to discover the underlying semantic priors of individuals. By segmenting the crowd image into patches, this paper proposes the Patch-based Topic Model (PTM) for group detection. The main contributions of this study are threefold: (1) the crowd dynamics are represented by patch-level descriptor, which provides a macroscopic-level representation; (2) the semantic topic label of each patch are inferred by integrating the Latent Dirichlet Allocation (LDA) model and the Markov Random Fields (MRF); (3) the optimal group number is determined automatically with an intro-class distance evaluation criterion. Experimental results on real-world crowd videos demonstrate the superior performance of the proposed method over the state-of-the-arts. |
WOS关键词 | CROWD |
WOS研究方向 | Computer Science |
语种 | 英语 |
WOS记录号 | WOS:000415021600009 |
资助机构 | National Key Research and Development Program of China(2017YFB1002202) ; National Natural Science Foundation of China(61773316 ; Fundamental Research Funds for the Central Universities(3102017AX010) ; Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences ; 61379094) |
内容类型 | 期刊论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/29379] |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
作者单位 | 1.Northwestern Polytech Univ, Sch Comp Sci, Xian 710072, Shaanxi, Peoples R China 2.Northwestern Polytech Univ, Ctr Opt Imagery Anal & Learning, Xian 710072, Shaanxi, Peoples R China 3.Northwestern Polytech Univ, Unmanned Syst Res Inst, Xian 710072, Shaanxi, Peoples R China 4.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr Opt Imagery Anal & Learning, Xian 710119, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Chen, Mulin,Wang, Qi,Li, Xuelong. Patch-based topic model for group detection[J]. SCIENCE CHINA-INFORMATION SCIENCES,2017,60(11). |
APA | Chen, Mulin,Wang, Qi,&Li, Xuelong.(2017).Patch-based topic model for group detection.SCIENCE CHINA-INFORMATION SCIENCES,60(11). |
MLA | Chen, Mulin,et al."Patch-based topic model for group detection".SCIENCE CHINA-INFORMATION SCIENCES 60.11(2017). |
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