A two-stage hybrid approach to the correspondence problem via forward-searching and backward-correcting

A two-stage solution to the problem of the correspondence of points for motion estimation in computer vision is presented. The first stage of the algorithm is a sequential forward-searching algorithm (FSA), which extends all the survivor trajectories. The second stage of the algorithm is a batch-type, rule-based, backward-correcting algorithm (BCA). Under the simple error assumption (no chain errors), seven rules are sufficient to handle all the possible errors made by the FSA. The BCA takes the last four frames of points as input and rearranges the correspondence among them according to these rules. The FSA and BCA are applied alternatively. This algorithm is able to establish the correspondence of a sequence of frames of points without assuming that the numbers of points in all frames are equal or that the correspondence of the first two frames has been established. Experiments illustrate the robustness of the algorithm on sequences of synthetic data as well as on real images