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ICPR
2008
IEEE
14 years 6 months ago
Illumination invariants based on Markov random fields
We propose textural features, which are invariant to illumination spectrum and extremely robust to illumination direction. They require only a single training image per texture an...
Pavel Vacha, Michal Haindl
CVPR
2005
IEEE
14 years 7 months ago
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data
We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalb...
CVPR
2007
IEEE
14 years 7 months ago
Region Classification with Markov Field Aspect Models
Considerable advances have been made in learning to recognize and localize visual object classes. Simple bag-offeature approaches label each pixel or patch independently. More adv...
Jakob J. Verbeek, Bill Triggs
3DOR
2008
13 years 7 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
PAMI
2010
396views more  PAMI 2010»
13 years 3 months ago
Self-Validated Labeling of Markov Random Fields for Image Segmentation
—This paper addresses the problem of self-validated labeling of Markov random fields (MRFs), namely to optimize an MRF with unknown number of labels. We present graduated graph c...
Wei Feng, Jiaya Jia, Zhi-Qiang Liu