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» Markov Random Field Modeling in Computer Vision
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CVPR
2010
IEEE
14 years 1 months ago
Facial Point Detection using Boosted Regression and Graph Models
Finding fiducial facial points in any frame of a video showing rich naturalistic facial behaviour is an unsolved problem. Yet this is a crucial step for geometric-featurebased fa...
Michel Valstar, Brais Martinez, Xavier Binefa, Maj...
ECCV
2002
Springer
14 years 9 months ago
Stereo Matching Using Belief Propagation
In this paper, we formulate the stereo matching problem as a Markov network consisting of three coupled Markov random fields (MRF's). These three MRF's model a smooth fie...
Jian Sun, Heung-Yeung Shum, Nanning Zheng
ISVC
2010
Springer
13 years 6 months ago
Markov Random Field-Based Clustering for the Integration of Multi-view Range Images
Abstract. Multi-view range image integration aims at producing a single reasonable 3D point cloud. The point cloud is likely to be inconsistent with the measurements topologically ...
Ran Song, Yonghuai Liu, Ralph R. Martin, Paul L. R...
ATAL
2008
Springer
13 years 9 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 ...
CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)