A context dependent distance measure for shape clustering

Abstract

We present a new similarity measure between a single shape and a shape group as a basis for shape clustering following the paradigm of context dependent shape comparison: clusters are generated in the context of a reference shape, defined by the query shape it is compared to. Tightly coupled, the distance measure is the basis for a soft k-means like framework to achieve robust clustering. Successful application of the system along with generation of shape prototypes is demonstrated in comparison to latest approaches using elastic deformation. © 2008 Springer Berlin Heidelberg.