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» Modeling Image Textures by Gibbs Random Fields
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136
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ICMCS
2009
IEEE
415views Multimedia» more  ICMCS 2009»
14 years 8 months ago
A new localized superpixel Markov random field for image segmentation
In this paper, we present a novel localized Markov random field (MRF) method based on superpixels for region segmentation. Early vision problems could be formulated as pixel label...
Xiaofeng Wang, Xiao-Ping Zhang
98
Voted
ICPR
2004
IEEE
15 years 11 months ago
A Hybrid Face Recognition Method using Markov Random Fields
We propose a hybrid face recognition method that combines holistic and feature analysis-based approaches using a Markov random field (MRF) model. The face images are divided into ...
Dimitris N. Metaxas, Rui Huang, Vladimir Pavlovic
88
Voted
MICCAI
2009
Springer
15 years 11 months ago
A Conditional Random Field Approach for Coupling Local Registration with Robust Tissue and Structure Segmentation
Abstract. We consider a general modelling strategy to handle in a unified way a number of tasks essential to MR brain scan analysis. Our approach is based on the explicit definitio...
Benoit Scherrer, Florence Forbes, Michel Dojat
ICIP
2001
IEEE
15 years 11 months ago
DWT based non-parametric texture modeling
We propose a non-parametric texture modeling and synthesis technique based on the integer version of the Discrete Wavelet Transform (DWT). The successive levels of the DWT pyramid...
Gloria Menegaz
94
Voted
ICIP
2008
IEEE
15 years 4 months ago
Stochastic fusion of multi-view gradient fields
Image gradients form powerful cues in a host of vision and graphics applications. In this paper, we consider multiple views of a textured planar scene and consider the problem of ...
Aswin C. Sankaranarayanan, Rama Chellappa