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ICML
2009
IEEE
14 years 8 months ago
Exploiting sparse Markov and covariance structure in multiresolution models
We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR ...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
ICASSP
2011
IEEE
12 years 11 months ago
A general Bayesian algorithm for visual object tracking based on sparse features
This paper describes a Bayesian algorithm for rigid/non-rigid 2D visual object tracking based on sparse image features. The algorithm is inspired by the way human visual cortex se...
Mauricio Soto Alvarez, Carlo S. Regazzoni
EUROGRAPHICS
2010
Eurographics
14 years 4 months ago
Adding Depth to Cartoons Using Sparse Depth (In)equalities
This paper presents a novel interactive approach for adding depth information into hand-drawn cartoon images and animations. In comparison to previous depth assignment techniques ...
Daniel Sýkora, David Sedlacek, Sun Jinchao, John ...
BIBE
2008
IEEE
137views Bioinformatics» more  BIBE 2008»
14 years 2 months ago
A sparse variational Bayesian approach for fMRI data analysis
— The aim of this work is to propose a new approach for the determination of the design matrix in fMRI experiments. The design matrix embodies all available knowledge about exper...
Vangelis P. Oikonomou, Evanthia E. Tripoliti, Dimi...
TMI
2010
165views more  TMI 2010»
13 years 6 months ago
Spatio-Temporal Data Fusion for 3D+T Image Reconstruction in Cerebral Angiography
—This paper provides a framework for generating high resolution time sequences of 3D images that show the dynamics of cerebral blood flow. These sequences have the potential to ...
Andrew Copeland, Rami Mangoubi, Mukund N. Desai, S...