We introduce the notion of consensus skeletons for non-rigid space-time registration of a deforming shape. Instead of basing the registration on point features, which are local an...
Qian Zheng, Andrei Sharf, Andrea Tagliasacchi, Bao...
To automatically register foreground target in cluttered images, we present a novel hierarchical graph representation and a stochastic computing strategy in Bayesian framework. Th...
Xiaobai Liu, Liang Lin, Hongwei Li, Hai Jin, Wenbi...
Abstract. This paper describes a novel approach to automatically recover accurate correspondence over various shapes. In order to detect the features points with the capability in ...
A Bayesian network formulation for relational shape matching is presented. The main advantage of the relational shape matching approach is the obviation of the non-rigid spatial m...
Anand Rangarajan, James M. Coughlan, Alan L. Yuill...
This paper presents a general learning framework for non-rigid registration of MR brain images. Given a set of training MR brain images, three major types of information are partic...