Group action recognition in soccer videos

Group action recognition in soccer videos is a challenging problem due to the difficulties of group action representation and camera motion estimation. This paper presents a novel approach for recognizing group action with a moving camera. In our approach, egomotion is estimated by the Kanade-Lucas-Tomasi feature sets on successive frames. The optical flow is then computed on compensated frames. Due to the inaccurate ego-motion estimation, the optical flow can not reflect accurate motion of objects. In this paper, we propose a new motion descriptor which treats the optical flow as spatial patterns and extracts accurate global motion from the noisy optical flow. The Latent-Dynamic Conditional Random Field model is employed to recognize group action. Experimental results show that our approach is promising.

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Qingdi Wei, Weiming Hu, Xiaoqin Zhang, Yu Kong, Yunde Jia
• Keywords: Camera Motion Estimation, Computer Vision, ICPR 2008, Noisy Optical Flow, Optical Flow