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
Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-N...
Dror Baron, Shriram Sarvotham, Richard G. Baraniuk
Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analy...
Segmentation is a fundamental problem in medical image analysis. The use of prior knowledge is often considered to address the ill-posedness of the process. Such a process consists...
This paper presents a new formulation of the problem of motion estimation which attempts to give solutions to classical problems in the field, such as detection of motion disconti...