Improvement of an association algorithm for obstacle tracking

This article describes a modification of an association algorithm for object tracking based on the evidence theory. This association algorithm was first developed by Rombaut and subsequently improved in a general way by Gruyer. This algorithm has been modified here in order to obtain better results when data reliability is poor. This article presents the basic concepts of the evidence theory. Then, the association algorithm developed by Rombaut is explained, and some examples are given to show that this algorithm fails to give the proper decision when data reliability decreases. Finally, the new algorithm is presented and the two algorithms are compared using synthetic data. In order to test the robustness of the two algorithms, they were also tested using real data coming from a CCD camera and these data can be qualified as very noisy with a reliability ranging from good to very bad.