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» Markov Random Field Models in Computer Vision
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3DOR
2008
13 years 9 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
ICPR
2006
IEEE
14 years 8 months ago
Adaptative Markov Random Fields for Omnidirectional Vision
Images obtained with catadioptric sensors contain significant deformations which prevent the direct use of classical image treatments. Thus, Markov Random Fields (MRF) whose usefu...
Cédric Demonceaux, Pascal Vasseur
ECCV
2002
Springer
14 years 9 months ago
Factorial Markov Random Fields
In this paper we propose an extension to the standard Markov Random Field (MRF) model in order to handle layers. Our extension, which we call a Factorial MRF (FMRF), is analogous t...
Junhwan Kim, Ramin Zabih
ICCV
2009
IEEE
1048views Computer Vision» more  ICCV 2009»
15 years 11 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...
ICPR
2008
IEEE
14 years 1 months ago
Face super-resolution using 8-connected Markov Random Fields with embedded prior
In patch based face super-resolution method, the patch size is usually very small, and neighbor patches’ relationship via overlapped regions is only to keep smoothness of recons...
Kai Guo, Xiaokang Yang, Rui Zhang, Guangtao Zhai, ...