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.
The method in REF represents trajectories of pair-vehicles as a series of heat sources; then, a thermal diffusion process creates an activity map (or 2D matrix).
A Heat-Map-based Algorithm for Recognizing Group Activities in Videos
IEEE Trans. Circuits and Systems for Video Technology, vol. 23, no. 11, pp. 1980-1992, 2013
Computer Science