Body Detection and Tracking with Hierarchical Scheme in Dynamic Scenes

In this paper, we propose an approach for body detection and tracking with a hierarchical and salient-half-body-prior scheme and apply it in real dynamic scenes. The human region is firstly located by an SVM classifier with histogram of oriented gradients (HOG). Two image observations, motion foreground and edge distance map, are then applied for body detection. In detail, the torso part is first roughly initialized, and then parts are localized in a salient-prior half-body sampling scheme by maximizing body configuration probability with both parts likelihood and body geometry constraints. For body tracking, the color-texture appearance templates of parts extracted in detection phase are further used in tracking process. The approach has been tested on soccer and skating videos and got good results.