Fuzzy data association for image-based tracking in dense scenarios

A new approach for data association problems in video image sequences is presented, which uses JPDA formulation adapted to cope with video data peculiarities. A correlation level is computed to weight each blob contribution to each track, by means of a fuzzy system integrating different heuristics inferred from system performance under real situations. Results obtained in representative ground operations show the system capabilities to solve complex scenarios and improve tracking accuracy.