Abstract
Occlusion is a difficult problem for visual tracking and we use multiple wide baseline cameras to deal with occlusion. We propose a data fusion approach for visual tracking using multiple cameras with overlapping fields of view. First, we present a spatial and temporal recursive Bayesian filter to fuse information from multiple cameras. An adaptive particle filter is formulated to realize the spatial and temporal recursive Bayesian filter. Our algorithm is able to recover the target's position even under complete occlusion in a camera.