Object tracking using adaptive block matching

We propose an object-tracking algorithm that predicts the object contour using motion vector information. Tracking is achieved by predicting the object boundary using motion vectors, followed by contour update, using occlusions/disocclusion detection. An adaptive block-based approach has been used for estimating motion between frames. An efficient modulation scheme is used to control the gap between frames used for object tracking. The algorithm for detecting occlusions proceeds in two steps. First, covered regions are estimated from the displaced frame difference. These covered regions are classified into actual occlusions and false alarms using motion characteristics. Disocclusion detection is also performed in a similar manner. The immediate applications of the proposed tracking algorithm are video compression using MPEG-4 and content retrieval based on standards like H.26L. Preliminary simulation results demonstrate the performance of the proposed algorithm.