This paper is devoted to piecewise-constant segmentation of images using a curve evolution approach in a variational formulation. The problem to be solved is also called the minima...
In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
In this paper we incorporate recent results from AM-FM models for texture analysis into the variational model of image segmentation and examine the potential benefits of using the...
In this paper, we propose a novel motion vector processing approach based on the temporal analysis of motion vector reliability for motion-compensated frame interpolation. We firs...
We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang