Object tracking based on optical flow and depth

This paper describes a method to track an object based on optical flow and depth. The velocity and the depth of the target object are estimated from the histograms of the velocity and that of the disparity. A target region is extracted by Baysian inference using optical flow, disparity and the predicted target location. This method works even if tracking with either velocity data or disparity data alone may fail. Occlusion of the target can also be detected from the abrupt change of the disparity of the target region. Our method successfully tracked a moving person using a real image sequence.