A particle filter for joint detection and tracking of color objects

Czyz, Jacek Ristic, Branko Macq, Benoît [UCL]

Color is a powerful feature for tracking deformable objects in image sequences with complex backgrounds. The color particle filter has proven to be an efficient, simple and robust tracking algorithm. In this paper, we present a hybrid valued sequential state estimation algorithm, and its particle filter-based implementation, that extends the standard color particle filter in two ways. First, target detection and deletion are embedded in the particle filter without relying on an external track initialization and cancellation algorithm. Second, the algorithm is able to track multiple objects sharing the same color description while keeping the attractive properties of the original color particle filter. The performance of the proposed filter are evaluated qualitatively on various real-world video sequences with appearing and disappearing targets. (c) 2006 Elsevier B.V. All rights reserved.