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ICPR
2002
IEEE
15 years 10 months ago
Face Detection and Synthesis Using Markov Random Field Models
Markov Random Fields (MRFs) are proposed as viable stochastic models for the spatial distribution of gray level intensities for images of human faces. These models are trained usi...
Sarat C. Dass, Anil K. Jain, Xiaoguang Lu
CEC
2005
IEEE
15 years 3 months ago
Incorporating a Metropolis method in a distribution estimation using Markov random field algorithm
Abstract- Markov Random Field (MRF) modelling techniques have been recently proposed as a novel approach to probabilistic modelling for Estimation of Distribution Algorithms (EDAs)...
Siddhartha Shakya, John A. W. McCall, Deryck F. Br...
ATAL
2008
Springer
14 years 11 months ago
Multi-robot Markov random fields
We propose Markov random fields (MRFs) as a probabilistic mathematical model for unifying approaches to multi-robot coordination or, more specifically, distributed action selectio...
Jesse Butterfield, Odest Chadwicke Jenkins, Brian ...
ICCV
2007
IEEE
15 years 11 months ago
LogCut - Efficient Graph Cut Optimization for Markov Random Fields
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...
Victor S. Lempitsky, Carsten Rother, Andrew Blake
ICIP
2005
IEEE
15 years 11 months ago
A segmentation method using compound Markov random fields based on a general boundary model
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 ...
Jue Wu, Albert C. S. Chung