A Heat-Map-Based Algorithm for Recognizing Group Activities in Videos
In this paper, a new heat-map-based algorithm is proposed for group activity recognition. The proposed algorithm first models human trajectories as series of heat sources and then applies a thermal diffusion process to create a heat map (HM) for representing the group activities. Based on this HM, a...
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          | Published in | IEEE transactions on circuits and systems for video technology Vol. 23; no. 11; pp. 1980 - 1992 | 
|---|---|
| Main Authors | , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        New York, NY
          IEEE
    
        01.11.2013
     Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 1051-8215 1558-2205  | 
| DOI | 10.1109/TCSVT.2013.2269780 | 
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| Abstract | In this paper, a new heat-map-based algorithm is proposed for group activity recognition. The proposed algorithm first models human trajectories as series of heat sources and then applies a thermal diffusion process to create a heat map (HM) for representing the group activities. Based on this HM, a new key-point-based (KPB) method is used for handling the alignments among HMs with different scales and rotations. A surface-fitting (SF) method is also proposed for recognizing group activities. Our proposed HM feature can efficiently embed the temporal motion information of the group activities while the proposed KPB and SF methods can effectively utilize the characteristics of the HM for activity recognition. Section IV demonstrates the effectiveness of our proposed algorithms. | 
    
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| AbstractList | In this paper, a new heat-map-based algorithm is proposed for group activity recognition. The proposed algorithm first models human trajectories as series of heat sources and then applies a thermal diffusion process to create a heat map (HM) for representing the group activities. Based on this HM, a new key-point-based (KPB) method is used for handling the alignments among HMs with different scales and rotations. A surface-fitting (SF) method is also proposed for recognizing group activities. Our proposed HM feature can efficiently embed the temporal motion information of the group activities while the proposed KPB and SF methods can effectively utilize the characteristics of the HM for activity recognition. Section IV demonstrates the effectiveness of our proposed algorithms. | 
    
| Author | Weiyao Lin Bin Sheng Zhenzhong Chen Hang Chu Jianxin Wu  | 
    
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| Keywords | Performance evaluation Thermal diffusion heat map Gesture recognition Activity levels group activity Algorithm Heat source surface matching Multiscale method A posteriori estimation Diffusion process Activity recognition Curve fitting  | 
    
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| SubjectTerms | Activity recognition Applied sciences Diffusion processes Exact sciences and technology Feature extraction group activity heat map Heating Information, signal and communications theory Pattern recognition Signal processing surface matching Surface treatment Telecommunications and information theory Trajectory Videos  | 
    
| Title | A Heat-Map-Based Algorithm for Recognizing Group Activities in Videos | 
    
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