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» Markov Random Field Modeling in Computer Vision
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ICPR
2006
IEEE
14 years 8 months ago
Detecting Coarticulation in Sign Language using Conditional Random Fields
Coarticulation is one of the important factors that makes automatic sign language recognition a hard problem. Unlike in speech recognition, coarticulation effects in sign language...
Ruiduo Yang, Sudeep Sarkar
ICPR
2008
IEEE
14 years 9 months ago
Change detection based on adaptive Markov Random Fields
Usually changes in remote sensing images go along with the appearance or disappearance of some edges. In addition, pixels located along the edges are likely to weakly influenced b...
Chunlei Huo, Hanqing Lu, Jian Cheng, Keming Chen, ...
CVPR
2011
IEEE
13 years 4 months ago
Inference for Order Reduction in Markov Random Fields
This paper presents an algorithm for order reduction of factors in High-Order Markov Random Fields (HOMRFs). Standard techniques for transforming arbitrary high-order factors in...
Andrew C. Gallagher, Dhruv Batra, Devi Parikh
CVPR
2009
IEEE
15 years 2 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
CVPR
2005
IEEE
14 years 9 months ago
Fields of Experts: A Framework for Learning Image Priors
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
Stefan Roth, Michael J. Black