This paper addresses the problem of segmenting a textured mesh into objects or object classes, consistently with user-supplied seeds. We view this task as transductive learning and...
In this paper a new and efficient supervised method for color image segmentation is presented. This method improves a part of the automatic extraction problem. The basic technique...
Given a sequence of observable features of a linear dynamical system (LDS), we propose the problem of finding a representation of the LDS which is sparse in terms of a given dict...
We present a novel representation for modeling textured
regions subject to smooth variations in orientation and
scale. Utilizing the steerable pyramid of Simoncelli and
Freeman ...
In this paper, we propose a Markov random field (MRF) image segmentation model which aims at combining color and texture features. The theoretical framework relies on Bayesian est...