A Heat-Map-based Algorithm for Recognizing Group Activities in Videos

• Published in: arXiv.org
• Main Authors: Lin, Weiyao, Chu, Hang, Wu, Jianxin, Sheng, Bin, Chen, Zhenzhong
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 21.02.2015
• Subjects: Activity recognition; Algorithms; Computer Science - Computer Vision and Pattern Recognition; Graphical representations; Heat sources; Thermal diffusion
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.1502.06076

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.