Abstract

This paper proposes Motion Structure Tracker (MST) to solve the problem of tracking in very crowded structured scenes. It com- bines visual tracking, motion pattern learning and multi-target tracking. Tracking in crowded scenes is very challenging due to hundreds of similar ob jects, cluttered background, small ob ject size, and occlusions. How- ever, structured crowded scenes exhibit clear motion pattern(s), which provides rich prior information. In MST, tracking and detection are per- formed jointly, and motion pattern information is integrated in both steps to enforce scene structure constraint. MST is initially used to track a single target, and further extended to solve a simplified version of the multi-target tracking problem. Experiments are performed on real-world challenging sequences, and MST gives promising results. Our method significantly outperforms several state-of-the-art methods both in terms of track ratio and accuracy.