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ICB
2009
Springer
412views Biometrics» more  ICB 2009»
14 years 2 months ago
Bayesian Face Recognition Based on Markov Random Field Modeling
In this paper, a Bayesian method for face recognition is proposed based on Markov Random Fields (MRF) modeling. Constraints on image features as well as contextual relationships be...
Rui Wang, Zhen Lei, Meng Ao, Stan Z. Li
ICIP
1995
IEEE
14 years 9 months ago
3D super-resolution using generalized sampling expansion
A 3D super-resolution algorithm is proposed below, based on a probabilistic interpretation of the ndimensional version of Papoulis' generalized sampling theorem. The algorith...
Hassan Shekarforoush, Marc Berthod, Josiane Zerubi...
ICIP
2010
IEEE
13 years 5 months ago
3D augmented Markov random field for object recognition
In this paper, we propose to use 3D information to augment the Markov random field (MRF) model for object recognition. Conventional MRF for image-based object recognition usually ...
Wei Yu, Ahmed Bilal Ashraf, Yao-Jen Chang, Congcon...
ICDAR
2009
IEEE
13 years 5 months ago
Unconstrained Handwritten Document Layout Extraction Using 2D Conditional Random Fields
The paper describes a new approach using a Conditional Random Fields (CRFs) to extract physical and logical layouts in unconstrained handwritten letters such as those sent by indi...
Florent Montreuil, Emmanuele Grosicki, Laurent Heu...
3DOR
2008
13 years 10 months ago
Markov Random Fields for Improving 3D Mesh Analysis and Segmentation
Mesh analysis and clustering have became important issues in order to improve the efficiency of common processing operations like compression, watermarking or simplification. In t...
Guillaume Lavoué, Christian Wolf