Detecting Motion Patterns in Dynamic Crowd Scenes

Detecting motion pattern in dynamic crowd scenes is a challenging problem in computer vision field. In this paper, we propose a novel approach to detect the motion patterns from global perspective. To extract the discriminative spatial-temporal features, we introduce the Motion History Image (MHI) into the optical flow algorithm. Motion patterns are then detected by automatic clustering of optical flow vectors through hierarchical clustering. Experiment evaluation on some challenging videos shows reliable detection results and demonstrates the effectiveness of our proposed approach.