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NIPS
2008
13 years 9 months ago
Sparse Signal Recovery Using Markov Random Fields
Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Ric...
VMV
2001
209views Visualization» more  VMV 2001»
13 years 9 months ago
A Novel Probabilistic Model for 3D Object Recognition: Spin-Glass Markov Random Fields
This contribution presents a new class of MRF, that is inspired by methods of statistical physics. The new energy function assumes full-connectivity in the neighborhood system and...
Barbara Caputo, Sahla Bouattour, Dietrich Paulus
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
MICCAI
2003
Springer
14 years 8 months ago
Regularization of Diffusion Tensor Maps Using a Non-Gaussian Markov Random Field Approach
Abstract. In this paper we propose a novel non-Gaussian MRF for regularization of tensor fields for fiber tract enhancement. Two entities are considered in the model, namely, the l...
Marcos Martín-Fernández, Carlos Albe...
ICCV
2009
IEEE
1048views Computer Vision» more  ICCV 2009»
15 years 16 days ago
Face Recognition With Contiguous Occlusion Using Markov Random Fields
Partially occluded faces are common in many applications of face recognition. While algorithms based on sparse representation have demonstrated promising results, they achieve t...
Zihan Zhou, Andrew Wagner, Hossein Mobahi, John Wr...