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» Markov Random Field Models in Computer Vision
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EMMCVPR
2007
Springer
14 years 1 months ago
Bayesian Inference for Layer Representation with Mixed Markov Random Field
Abstract. This paper presents a Bayesian inference algorithm for image layer representation [26], 2.1D sketch [6], with mixed Markov random field. 2.1D sketch is an very important...
Ru-Xin Gao, Tianfu Wu, Song Chun Zhu, Nong Sang
EMMCVPR
2001
Springer
13 years 12 months ago
Relaxing Symmetric Multiple Windows Stereo Using Markov Random Fields
This paper introduces R-SMW, a new algorithm for stereo
Andrea Fusiello, Umberto Castellani, Vittorio Muri...
ICPR
2006
IEEE
14 years 8 months ago
A Markovian Approach for Handwritten Document Segmentation
We address in this paper the problem of segmenting complex handritten pages such as novelist drafts or authorial manuscripts. We propose to use stochastic and contextual models in...
Stéphane Nicolas, Thierry Paquet, Laurent H...
ICPR
2010
IEEE
14 years 2 months ago
Continuous Markov Random Field Optimization using Fusion Move Driven Markov Chain Monte Carlo Technique
Many vision applications have been formulated as Markov Random Field (MRF) problems. Although many of them are discrete labeling problems, continuous formulation often achieves gre...
Wonsik Kim (Seoul National University), Kyoung Mu ...
ICCV
2007
IEEE
14 years 9 months ago
Steerable Random Fields
In contrast to traditional Markov random field (MRF) models, we develop a Steerable Random Field (SRF) in which the field potentials are defined in terms of filter responses that ...
Stefan Roth, Michael J. Black