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1894views
10 years 8 months ago
Supervised Image Segmentation Using Markov Random Fields
This is the sample implementation of a Markov random field based image segmentation algorithm described in the following papers: 1. Mark Berthod, Zoltan Kato, Shan Yu, and Josi...
Csaba Gradwohl, Zoltan Kato

Source Code
846views
10 years 8 months ago
Supervised Color Image Segmentation in a Markovian Framework
This is the sample implementation of a Markov random field based color image segmentation algorithm described in the following paper: Zoltan Kato, Ting Chuen Pong, and John Chu...
Mihaly Gara, Zoltan Kato
CVPR
2010
IEEE
1790views Computer Vision» more  CVPR 2010»
10 years 9 months ago
Data Driven Mean-Shift Belief Propagation For non-Gaussian MRFs
We introduce a novel data-driven mean-shift belief propagation (DDMSBP) method for non-Gaussian MRFs, which often arise in computer vision applications. With the aid of scale sp...
Minwoo Park, S. Kashyap, R. Collins, and Y. Liu
ICCV
2009
IEEE
11 years 6 months ago
Piecewise Planar Stereo for Image-based Rendering
We present a novel multi-view stereo method designed for image-based rendering that generates piecewise planar depth maps from an unordered collection of photographs. First a di...
Sudipta N. Sinha, Drew Steedly and Richard Szelisk...
ICCV
2009
IEEE
1048views Computer Vision» more  ICCV 2009»
11 years 6 months 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...
CVPR
2009
IEEE
11 years 8 months ago
Beyond Pairwise Energies: Efficient Optimization for Higher-order MRFs
In this paper, we introduce a higher-order MRF optimization framework. On the one hand, it is very general; we thus use it to derive a generic optimizer that can be applied to a...
Nikos Komodakis (University of Crete), Nikos Parag...
CVPR
2009
IEEE
11 years 8 months ago
Continuous Maximal Flows and Wulff Shapes: Application to MRFs
Convex and continuous energy formulations for low level vision problems enable efficient search procedures for the corresponding globally optimal solutions. In this work we exte...
Christopher Zach (UNC Chapel Hill), Marc Niethamme...
CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
11 years 8 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)
CVPR
2009
IEEE
11 years 8 months ago
A Revisit of Generative Model for Automatic Image Annotation using Markov Random Fields
Much research effort on Automatic Image Annotation (AIA) has been focused on Generative Model, due to its well formed theory and competitive performance as compared with many we...
Yu Xiang (Fudan University), Xiangdong Zhou (Fudan...
CVPR
2009
IEEE
11 years 8 months ago
Global Connectivity Potentials for Random Field Models
Markov random field (MRF, CRF) models are popular in computer vision. However, in order to be computationally tractable they are limited to incorporate only local interactions a...
Sebastian Nowozin, Christoph H. Lampert
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