Tracking multiple features using relaxation

摘要

A new algorithm is introduced for tracking multiple features in an image sequence. First, the proposed method iteratively reduces the disparity of each possible match by relaxation labeling. It is assumed that all trajectories are smooth and the smoothness is used as the measure for correspondence. Some cases of wrong correspondences can be recovered by a proposed scheme called constraint-aided exchange during the tracking process. Occluded or missing feature points can be detected and predicted in the proposed algorithm. Finally, the algorithm is applied to data obtained from real world scenes. The human motion analysis can be achieved by the tracking algorithm.