Markov Random Fields (MRFs) are ubiquitous in lowlevel computer vision. In this paper, we propose a new approach to the optimization of multi-labeled MRFs. Similarly to -expansion...
Markov random field (MRF) theory has widely been applied to segmentation in noisy images. This paper proposes a new MRF method. First, it couples the original labeling MRF with a ...
We describe a method for learning statistical models of images using a second-order hidden Markov mesh model. First, an image can be segmented in a way that best matches its stati...
Daniel DeMenthon, David S. Doermann, Marc Vuilleum...
This paper deals with the motion detection problem. This issue is of key importance in many application fields. To solve this problem, we compute the dominant motion in the sequen...
Protein chimerism is a phenomenon involving the combination of multiple ancestral sequences into a single, multi-domain protein through evolution. We propose a novel method for de...