We present a probabilistic approach to shape matching which is invariant to rotation, translation and scaling. Shapes are represented by unlabeled point sets, so discontinuous bou...
Modeling objects by probability density functions (pdf) is a new powerful method to represent complex objects in databases. By representing an object as a pdf, e.g. a Gaussian, it...
This article presents a method aiming at quantifying the visual similarity between an image and a class model. This kind of problem is recurrent in many applications such as objec...
Correspondence algorithms typically struggle with shapes that display part-based variation. We present a probabilistic approach that matches shapes using independent part transfor...
Abstract. In this paper we present a probabilistic algorithm which factorizes non-negative data. We employ entropic priors to additionally satisfy that user specified pairs of fac...
Paris Smaragdis, Madhusudana V. S. Shashanka, Bhik...