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» Markov Random Field Models in Computer Vision
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PAMI
2010
417views more  PAMI 2010»
14 years 8 months ago
Auto-Context and Its Application to High-Level Vision Tasks and 3D Brain Image Segmentation
The notion of using context information for solving high-level vision and medical image segmentation problems has been increasingly realized in the field. However, how to learn a...
Zhuowen Tu, Xiang Bai
CVPR
2007
IEEE
15 years 12 months ago
An MRF and Gaussian Curvature Based Shape Representation for Shape Matching
Matching and registration of shapes is a key issue in Computer Vision, Pattern Recognition, and Medical Image Analysis. This paper presents a shape representation framework based ...
Pengdong Xiao, Nick Barnes, Tibério S. Caet...
CVPR
2006
IEEE
15 years 3 months ago
Combined Depth and Outlier Estimation in Multi-View Stereo
In this paper, we present a generative model based approach to solve the multi-view stereo problem. The input images are considered to be generated by either one of two processes:...
Christoph Strecha, Rik Fransens, Luc J. Van Gool
EMNLP
2006
14 years 11 months ago
A Hybrid Markov/Semi-Markov Conditional Random Field for Sequence Segmentation
Markov order-1 conditional random fields (CRFs) and semi-Markov CRFs are two popular models for sequence segmentation and labeling. Both models have advantages in terms of the typ...
Galen Andrew

Publication
281views
16 years 9 months ago
Modeling Image Textures by Gibbs Random Fields
Drawbacks of the traditional scenario of image modeling by Gibbs random fields with multiple pairwise pixel interactions are outlined, and a more reasonable alternative scenario b...
Georgy Gimel'farb