Shape verification using belief updating

This paper addresses the problem of2D shape representation and its application to object verification. We show how knowledge of shape can be integrated in a principled manner with low-level evidence such as an estimate of object position and an edge strength map. We begin by considering the role of shape in image interpretation and discuss the criteria which should be applied in assessing representations of shape. We propose new criteria, particularly as regards the ability to model variability, and describe a Chord Length Distribution (CLD) representation of shape which possesses many desirable properties. We show how the CLD representation can be used in an iterative belief-updating scheme for object location and verification. We give experimental results which demonstrate the feasibility of the method and discuss future developments.