Motion tracking as a constrained optimization problem

In this paper we pose the problem of tracking of a varying number of points through an image sequence as a multi-objective optimization problem with additional hard constraints. One of the objectives is to find smooth tracks based on second-order motion characteristics optimized over several frames. The corresponding optimization algorithm we present is a sequential heuristic search algorithm that adequately prunes the search tree in such a way that its exponential order remains low. When the algorithm is compared to other tracking algorithms, it turns out that the proposed algorithm is easier to tune and generally more efficient and more accurate. (C) 2003 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.