Real-time multi-view 3D object tracking in cluttered scenes

This paper presents an approach to real-time 3D object tracking in cluttered scenes using multiple synchronized and calibrated cameras. The goal is to accurately track targets over a long period of time in the presence of complete occlusion in some of the camera views. In the proposed system, color histogram was used to represent object appearance. Tracked 3D object locations were smoothed and new locations predicted using a Kalman filter. The predicted object 3D location was then projected onto all camera views to provide a search region for robust 2D object tracking and occlusion detection. The experimental results were validated using ground-truth data obtained from a marker-based motion capture system. The results illustrate that the proposed approach is capable of effective and robust 3D tracking of multiple objects in cluttered scenes.