Recent work in supervised learning of term-based retrieval models has shown significantly improved accuracy can often be achieved via better model estimation [2, 10, 11, 17]. In ...
: Contour Estimation, Bayesian Estimation, Random Fields, Dynamic Programming, Multigrid Methods. This paper addresses contour estimation on images modeled as piecewise homogeneous...
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
We present a discriminative part-based approach for the recognition of object classes from unsegmented cluttered scenes. Objects are modeled as flexible constellations of parts co...
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...