Automatic mutual nonrigid registration of dense surfaces by graphical model based inference

Abstract

This paper addresses the problem of fully automatic matching two triangulated surface meshes. In this paper, a similarity measurement is constructed to measure the consistency of the constraints among the correspondent landmarks, which is rigid transformation immune and robust to nonrigid deformations. The matching problem is then solved by directly finding correspondence between the landmarks of the two surfaces by graphical model based Bayesian inference. In order to reduce the computational complexity and to accelerate the convergence, a hierarchical graphical model is constructed which enables mutual registration and information exchange between the two surfaces during registration. Experiments on randomly generated instances from a PCA based statistical model of proximal femurs verified the proposed approach. © 2008 Springer Berlin Heidelberg.