This paper proposes a unified framework for spatiotemporal segmentation of video sequences. A Bayesian network is presented to model the interactions among the motion vector field...
Markov random field (MRF, CRF) models are popular in
computer vision. However, in order to be computationally
tractable they are limited to incorporate only local interactions
a...
The paper describes a lexicon driven approach for word recognition on handwritten documents using Conditional Random Fields(CRFs). CRFs are discriminative models and do not make a...
Shravya Shetty, Harish Srinivasan, Sargur N. Sriha...
In this paper, we develop a model for representing term dependence based on Markov Random Fields and present an approach based on Markov Chain Monte Carlo technique for generating ...
Drawbacks of the traditional scenario of image modeling by Gibbs random fields with multiple pairwise pixel interactions are outlined, and a more reasonable alternative scenario b...