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MICCAI
2004
Springer
16 years 4 months ago
3D Bayesian Regularization of Diffusion Tensor MRI Using Multivariate Gaussian Markov Random Fields
3D Bayesian regularization applied to diffusion tensor MRI is presented here. The approach uses Markov Random Field ideas and is based upon the definition of a 3D neighborhood syst...
Marcos Martín-Fernández, Carl-Fredri...
CVPR
2010
IEEE
16 years 5 days ago
On improving point-based 3D recognition
We present a framework that retains ambiguity in feature matching to increase the performance of 3D object recognition systems. Whereas previous systems removed ambiguous correspo...
Edward Hsiao, Alvaro Collet, Martial Hebert
CA
2000
IEEE
15 years 8 months ago
Motion Processing using Variable Harmonic Components
This paper discusses the problem of motion processing and proposes the use of a mathematical model, which describes a motion signal as a path with variable harmonic components. We...
Jonas Gomes, Luiz Velho, Fernando Wagner da Silva,...
3DOR
2008
15 years 6 months ago
Markov Random Fields for Improving 3D Mesh Analysis and Segmentation
Mesh analysis and clustering have became important issues in order to improve the efficiency of common processing operations like compression, watermarking or simplification. In t...
Guillaume Lavoué, Christian Wolf
ICCV
2003
IEEE
15 years 9 months ago
Gamut Constrained Illuminant Estimation
This paper presents a novel solution to the illuminant estimation problem: the problem of how, given an image of a scene taken under an unknown illuminant, we can recover an estim...
Graham D. Finlayson, Steven D. Hordley, Ingeborg T...