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» Markov Random Fields with Efficient Approximations
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UAI
2004
13 years 9 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
ICML
2005
IEEE
14 years 8 months ago
Variational Bayesian image modelling
We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang
CVPR
1999
IEEE
13 years 12 months ago
A New Bayesian Framework for Object Recognition
We introduce an approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. This approach provides an effici...
Yuri Boykov, Daniel P. Huttenlocher
ECCV
2004
Springer
14 years 9 months ago
MCMC-Based Multiview Reconstruction of Piecewise Smooth Subdivision Curves with a Variable Number of Control Points
We investigate the automated reconstruction of piecewise smooth 3D curves, using subdivision curves as a simple but flexible curve representation. This representation allows taggin...
Michael Kaess, Rafal Zboinski, Frank Dellaert

Publication
222views
15 years 7 months ago
Quantitative Description of Spatially Homogeneous Textures by Characteristic Grey Level Co-Occurrences
Gibbs random eld model with multiple pairwise pixel interactions describes each type of spatially homogeneous image textures in terms of a pixel neighbourhood and Gibbs potentials...
Georgy Gimel'farb