A colour statistical approach to phantom pruning in multi-view detection

To increase the robustness of detection in intelligent video surveillance systems, homography has been widely used to fuse foreground regions projected from multiple camera views to a reference view. However, the intersections of non-corresponding foreground regions can cause phantoms. This paper proposes a colour statistical approach to cope with this problem. This method is based on the Mahalanobis distance between the colour patches which correspond to the same foreground region in the reference view. This method can overcome the problems in the pixelwise colour correlation approach.