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
In the context of variational image segmentation, we propose a new finite-dimensional implicit surface representation. The key idea is to span a subset of implicit functions with ...
Benoit Mory, Roberto Ardon, Anthony J. Yezzi, Jean...
This paper presents a method for incrementally segmenting images over time using both intensity and motion information. This is done by formulating a model of physically signi cant...
In this paper, we describe a region-based active contour technique to perform image segmentation. We propose an energy functional that realizes an explicit trade-off between the (...
Samuel Dambreville, Anthony J. Yezzi, Shawn Lankto...
A new concept and algorithm are presented for noniterative robust estimation of piecewise smooth curves of maximal edge strength in small image windows – typically ¢¡£ to...