Tracking distributions with an overlap prior

Recent studies have shown that embedding similarity/dissimilarity measures between distributions in the variational level set framework can lead to effective object segmentation/tracking algorithms. In this connection, existing methods assume implicitly that the overlap between the distributions of image data within the object and its background has to be minimal. Unfortunately, such assumption may not be valid in many important applications. This study investigates an overlap prior, which embeds knowledge about the overlap between the distributions of the object and the background in level set tracking. It consists of evolving a curve to delineate the target object in the current frame. The level set curve evolution equation is sought following the maximization of a functional containing three terms: (1) an original overlap prior which measures the conformity of overlap between the nonparametric (kernel-based) distributions within the object and the background to a learned descriptio...

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Ismail Ben Ayed, Shuo Li, Ian G. Ross
• Keywords: Computer Vision, Curve, Curve Evolution, CVPR 2008, Important Applications