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Particle filters have become a viable solution to the visual tracking problem as they are well suited for state estimation in the rich visual world where non-linear, non-Gaussian distributions are common and where information from various sensor sources must be fused. This paper introduces an adaptive particle filter framework in which the numbers of particles, fusion parameters, as well as filter...
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