A study of clustering applied to multiple target tracking algorithm

In this paper the effectiveness of two Data Association algorithms for Multiple Target Tracking (MTT) based on Global Nearest Neighbor approach are compared. As the time for assignment problem solution increases nonlinearly depending on the problem size, it is useful to divide the whole scenario on small groups of targets called clusters. For each cluster the assignment problem is solved by using-Munkres algorithm. Results reveal that the computational time especially for large scenarios decreases significantly when clustering is used.