Shape Context: A new descriptor for shape matching and object recognition

Abstract

We introduce a new shape descriptor, the shape context, for correspondence recovery and shape-based object recognition. The shape context at a point captures the distribution over relative positions of other shape points and thus summarizes global shape in a rich, local descriptor. Shape contexts greatly simplify recovery of correspondences between points of two given shapes. Moreover, the shape context leads to a robust score for measuring shape similarity, once shapes are aligned. The shape context descriptor is tolerant to all common shape deformations. As a key advantage no special landmarks or key-points are necessary. It is thus a generic method with applications in object recognition, image registration and point set matching. Using examples involving both handwritten digits and 3D objects, we illustrate its power for object recognition