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ECCV
2006
Springer
14 years 6 months ago
A Comparative Study of Energy Minimization Methods for Markov Random Fields
One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many early vision tasks require labeling each pixel with som...
Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...
PAMI
2008
198views more  PAMI 2008»
13 years 4 months ago
A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors
Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel-labeling tasks such as depth or texture computation....
Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...
ICASSP
2007
IEEE
13 years 11 months ago
Markov Random Field Energy Minimization via Iterated Cross Entropy with Partition Strategy
This paper introduces a novel energy minimization method, namely iterated cross entropy with partition strategy (ICEPS), into the Markov random field theory. The solver, which is...
Jue Wu, Albert C. S. Chung
CVPR
2009
IEEE
14 years 2 months ago
Markov Chain Monte Carlo Combined with Deterministic Methods for Markov Random Field Optimization
Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
MIA
2010
170views more  MIA 2010»
12 years 11 months ago
Linear intensity-based image registration by Markov random fields and discrete optimization
We propose a framework for intensity-based registration of images by linear transformations, based on a discrete Markov Random Field (MRF) formulation. Here, the challenge arises ...
Darko Zikic, Ben Glocker, Oliver Kutter, Martin Gr...