Point-wise Map Recovery and Refinement from Functional Correspondence

Since their introduction in the shape analysis community, functional maps have met with considerable success due to their ability to compactly represent dense correspondences between deformable shapes. Despite the numerous advantages of such representation, however, the problem of converting a given functional map back to a point-topoint map has received a surprisingly limited interest. In this paper we analyze the general problem of point-wise map recovery from arbitrary functional maps. In doing so, we rule out many of the assumptions required by the currently established approach – most notably, the limiting requirement of the input shapes being nearlyisometric. We devise an efficient recovery process based on a simple probabilistic model. Experiments confirm that this approach achieves remarkable accuracy improvements in very challenging cases.