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» Markov Random Field Modeling in Computer Vision
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ICML
2009
IEEE
14 years 10 months ago
Learning structurally consistent undirected probabilistic graphical models
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
Sushmita Roy, Terran Lane, Margaret Werner-Washbur...
CVPR
2009
IEEE
15 years 4 months ago
P-Brush: Continuous Valued MRFs with Normed Pairwise Distributions for Image Segmentation
Interactive image segmentation traditionally involves the use of algorithms such as Graph Cuts or Random Walker. Common concerns with using Graph Cuts are metrication artifacts ...
Dheeraj Singaraju, Leo Grady, René Vidal
CVPR
2011
IEEE
13 years 26 days ago
Connecting Non-Quadratic Variational Models and MRFs
Spatially-discrete Markov random fields (MRFs) and spatially-continuous variational approaches are ubiquitous in low-level vision, including image restoration, segmentation, opti...
Kevin Schelten, Stefan Roth
UAI
2004
13 years 10 months ago
From Fields to Trees
We present new MCMC algorithms for computing the posterior distributions and expectations of the unknown variables in undirected graphical models with regular structure. For demon...
Firas Hamze, Nando de Freitas
ICMCS
2007
IEEE
143views Multimedia» more  ICMCS 2007»
14 years 3 months ago
Hidden Conditional Random Fields for Meeting Segmentation
Automatic segmentation and classification of recorded meetings provides a basis towards understanding the content of a meeting. It enables effective browsing and querying in a me...
Stephan Reiter, Björn Schuller, Gerhard Rigol...