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» Modeling Image Textures by Gibbs Random Fields
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ICCV
2011
IEEE
14 years 16 days ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
148
Voted
AIPR
2005
IEEE
15 years 6 months ago
Face Recognition Using Multispectral Random Field Texture Models, Color Content, and Biometric Features
Most of the available research on face recognition has been performed using gray scale imagery. This paper presents a novel two-pass face recognition system that uses a Multispect...
Orlando J. Hernandez, Mitchell S. Kleiman
86
Voted
ICIP
2003
IEEE
16 years 2 months ago
Object localization using texture motifs and Markov random fields
This work presents a novel approach to object localization in complex imagery. In particular, the spatial extents of objects characterized by distinct spatial signatures at multip...
Shawn Newsam, Sitaram Bhagavathy, B. S. Manjunath
CVPR
2008
IEEE
16 years 2 months ago
Learning coupled conditional random field for image decomposition with application on object categorization
This paper proposes a computational system of object categorization based on decomposition and adaptive fusion of visual information. A coupled Conditional Random Field is develop...
Xiaoxu Ma, W. Eric L. Grimson
134
Voted
SCALESPACE
2007
Springer
15 years 6 months ago
Non-negative Sparse Modeling of Textures
This paper presents a statistical model for textures that uses a non-negative decomposition on a set of local atoms learned from an exemplar. This model is described by the varianc...
Gabriel Peyré