Color-Based multiple agent tracking for wireless image sensor networks
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
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Color as a distinct feature is widely used for object representation and tracking. However, color-based tracking is often influenced by clutter background and illumination variation. This paper presents a robust color-based tracking method, in which robust color feature is extracted for constructing observation model under the modified Particle Filter tracking framework. The object is represented by its dominant color, and the weighted histogram with spatial information of the dominant color is used to optimize object models. In the Particle Filter framework, an extended iterated likelihood weighting scheme is employed to utilize more valuable particles. The experimental results show it is a real-time robust tracker, and it can obtain more than 30fps with 2.4 G CPU and 512 M RAM.