We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a category o...
Three-dimensional geometric data play fundamental roles in many computer vision applications. However, their scale-dependent nature, i.e. the relative variation in the spatial ext...
This paper presents a novel motion segmentation algorithm on the basis of mixture of Dirichlet process (MDP) models, a kind of nonparametric Bayesian framework. In contrast to pre...
Many current face recognition algorithms perform badly when the lighting or pose of the probe and gallery images differ. In this paper we present a novel algorithm designed for th...
In many computer vision applications, such as face recognition and hand pose estimation, we need systems that can recognize a very large number of classes. Large margin classifica...
Vassilis Athitsos, Alexandra Stefan, Quan Yuan, St...