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CVPR
2004
IEEE
14 years 6 months ago
A Graphical Model Framework for Coupling MRFs and Deformable Models
This paper proposes a new framework for image segmentation based on the integration of MRFs and deformable models using graphical models. We first construct a graphical model to r...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
JMLR
2010
105views more  JMLR 2010»
12 years 11 months ago
Collective Inference for Extraction MRFs Coupled with Symmetric Clique Potentials
Many structured information extraction tasks employ collective graphical models that capture interinstance associativity by coupling them with various clique potentials. We propos...
Rahul Gupta, Sunita Sarawagi, Ajit A. Diwan
TOG
2008
197views more  TOG 2008»
13 years 4 months ago
Two-way coupling of fluids to rigid and deformable solids and shells
We propose a novel solid/fluid coupling method that treats the coupled system in a fully implicit manner making it stable for arbitrary time steps, large density ratios, etc. In c...
Avi Robinson-Mosher, Tamar Shinar, Jon Gretarsson,...
CVPR
2008
IEEE
14 years 6 months ago
Optical flow estimation with uncertainties through dynamic MRFs
In this paper, we propose a novel dynamic discrete framework to address image morphing with application to optical flow estimation. We reformulate the problem using a number of di...
Ben Glocker, Nikos Paragios, Nikos Komodakis, Geor...
ICCV
2009
IEEE
13 years 2 months ago
Segmentation, ordering and multi-object tracking using graphical models
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...
Chaohui Wang, Martin de La Gorce, Nikos Paragios