In this paper, we use large neighborhood Markov random fields to learn rich prior models of color images. Our approach extends the monochromatic Fields of Experts model (Roth &...
Alex J. Smola, Julian John McAuley, Matthias O. Fr...
This paper presents an overview of our recent work on managing image and video data. The first half of the paper describes a representation for the semantic spatial layout of vide...
Shawn D. Newsam, Jelena Tesic, Lei Wang, B. S. Man...
Abstract. In this paper we give a new model for foreground-background-shadow separation. Our method extracts the faithful silhouettes of foreground objects even if they have partly...
In this paper we address the problem of fast segmenting moving objects in video acquired by moving camera or more generally with a moving background. We present an approach based ...
Maximum a posteriori (MAP) filtering using the HuberMarkov random field (HMRF) image model has been shown in the past to be an effective method of reducing compression artifacts i...