A particle filter for joint detection and tracking of color objects

Authors:
Jacek Czyz;Branko Ristic;Benoit Macq
Affiliations:
Communications Laboratory, Université catholique de Louvain, Place du Levant 2, 1348 Louvain-la-Neuve, Belgium;ISRD, DSTO, 200 Labs, P.O. Box 1500, Edinburgh, SA 5111, Australia;Communications Laboratory, Université catholique de Louvain, Place du Levant 2, 1348 Louvain-la-Neuve, Belgium
Venue:
Image and Vision Computing
Year:
2007

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Abstract

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.