We present a novel approach to image segmentation using iterated Graph Cuts based on multi-scale smoothing. We compute the prior probability obtained by the likelihood from a color...
Abstract. We present a method to perform model selection based on predictive density in a class of spatio-temporal dynamic generalized linear models for areal data. These models as...
Given a Poisson process on a d-dimensional torus, its random geometric simplicial complex is the complex whose vertices are the points of the Poisson process and simplices are give...
In this study, we investigate online Bayesian estimation of the measurement noise density of a given state space model using particle filters and Dirichlet process mixtures. Diri...
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...