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» Markov Random Field Modeling in Computer Vision
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ICPR
2010
IEEE
13 years 8 months ago
Face Recognition At-A-Distance Using Texture, Dense and Sparse-Stereo Reconstruction
This paper introduces a framework for long-distance face recognition using dense and sparse stereo reconstruction, with texture of the facial region. Two methods to determine corr...
Ham Rara, Asem Ali, Shireen Elhabian, Aly A. Farag
ICPR
2010
IEEE
14 years 24 days ago
Scene Text Extraction with Edge Constraint and Text Collinearity
In this paper, we propose a framework for isolating text regions from natural scene images. The main algorithm has two functions: it generates text region candidates, and it veriļ...
Seonghun Lee, Kyomin Jung, Jin Hyung Kim
ICCV
2011
IEEE
12 years 9 months ago
Decision Tree Fields
This paper introduces a new formulation for discrete image labeling tasks, the Decision Tree Field (DTF), that combines and generalizes random forests and conditional random ļ¬el...
Sebastian Nowozin, Carsten Rother, Shai Bagon, Ban...
ICPR
2004
IEEE
14 years 10 months ago
Type-2 Fuzzy Hidden Markov Models to Phoneme Recognition
This paper presents a novel extension of Hidden Markov Models (HMMs): type-2 fuzzy HMMs (type-2 FHMMs). The advantage of this extension is that it can handle both randomness and f...
Jia Zeng, Zhi-Qiang Liu
ICCV
2005
IEEE
14 years 11 months ago
Globally Optimal Solutions for Energy Minimization in Stereo Vision Using Reweighted Belief Propagation
A wide range of low level vision problems have been formulated in terms of finding the most probable assignment of a Markov Random Field (or equivalently the lowest energy configu...
Talya Meltzer, Chen Yanover, Yair Weiss