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» Decomposition of range images using markov random fields
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IJISTA
2008
99views more  IJISTA 2008»
13 years 8 months ago
Increasing depth lateral resolution based on sensor fusion
Abstract: Technologies for measuring range data were intensively developed in recent years. The time-of-flight matrix range sensor is one of the most active range acquisition devic...
W. Hannemann, André Linarth, B. Liu, Gabrie...
ICPR
2002
IEEE
14 years 9 months ago
A General Multichannel Image Restoration Method Using Compound Models
In this paper we present a multichannel image restoration method using Compound Gauss Markov Random Field (CGMRF) models. Information regarding the objects present in the scene is...
Rafael Molina, Javier Mateos, Aggelos K. Katsaggel...
IJCV
2006
161views more  IJCV 2006»
13 years 8 months ago
Discriminative Random Fields
In this research we address the problem of classification and labeling of regions given a single static natural image. Natural images exhibit strong spatial dependencies, and mode...
Sanjiv Kumar, Martial Hebert
MICCAI
2008
Springer
14 years 10 months ago
Nonrigid Registration of Dynamic Renal MR Images Using a Saliency Based MRF Model
Nonrigid registration of contrast-enhanced MR images is a difficult problem due to the change in pixel intensity caused by the washin and wash-out of the contrast agent. In this pa...
Dwarikanath Mahapatra, Ying Sun
SIAMIS
2010
378views more  SIAMIS 2010»
13 years 3 months ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert