A Heat-Map-based Algorithm for Recognizing Group Activities in Videos
In this paper, a new heat-map-based (HMB) 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. B...
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| Published in | arXiv.org |
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| Main Authors | , , , , |
| Format | Paper Journal Article |
| Language | English |
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Ithaca
Cornell University Library, arXiv.org
21.02.2015
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| ISSN | 2331-8422 |
| DOI | 10.48550/arxiv.1502.06076 |
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| Abstract | In this paper, a new heat-map-based (HMB) 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 heat map, a new key-point based (KPB) method is used for handling the alignments among heat maps with different scales and rotations. And 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 heat map for activity recognition. Experimental results demonstrate the effectiveness of our proposed algorithms. |
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| AbstractList | In this paper, a new heat-map-based (HMB) 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 heat map, a new key-point based (KPB) method is used for handling the alignments among heat maps with different scales and rotations. And 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 heat map for activity recognition. Experimental results demonstrate the effectiveness of our proposed algorithms. IEEE Trans. Circuits and Systems for Video Technology, vol. 23, no. 11, pp. 1980-1992, 2013 In this paper, a new heat-map-based (HMB) 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 heat map, a new key-point based (KPB) method is used for handling the alignments among heat maps with different scales and rotations. And 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 heat map for activity recognition. Experimental results demonstrate the effectiveness of our proposed algorithms. |
| Author | Chu, Hang Wu, Jianxin Lin, Weiyao Sheng, Bin Chen, Zhenzhong |
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| BackLink | https://doi.org/10.48550/arXiv.1502.06076$$DView paper in arXiv https://doi.org/10.1109/TCSVT.2013.2269780$$DView published paper (Access to full text may be restricted) |
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| Snippet | In this paper, a new heat-map-based (HMB) algorithm is proposed for group activity recognition. The proposed algorithm first models human trajectories as... IEEE Trans. Circuits and Systems for Video Technology, vol. 23, no. 11, pp. 1980-1992, 2013 In this paper, a new heat-map-based (HMB) algorithm is proposed for... |
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| SubjectTerms | Activity recognition Algorithms Computer Science - Computer Vision and Pattern Recognition Graphical representations Heat sources Thermal diffusion |
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| Title | A Heat-Map-based Algorithm for Recognizing Group Activities in Videos |
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