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» Continuous Gaussian Mixture Modeling
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CVPR
2008
IEEE
15 years 12 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
DSMML
2004
Springer
15 years 3 months ago
Extensions of the Informative Vector Machine
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
Neil D. Lawrence, John C. Platt, Michael I. Jordan
ICIAP
2007
ACM
15 years 4 months ago
Rigid Image Registration based on Pixel Grouping
We propose a pixel similarity-based algorithm enabling accurate rigid registration between single and multimodal images. The method relies on the partitioning of a reference image...
Demetrios Gerogiannis, Christophoros Nikou, Aristi...
IJAR
2010
97views more  IJAR 2010»
14 years 8 months ago
Parameter estimation and model selection for mixtures of truncated exponentials
Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing ...
Helge Langseth, Thomas D. Nielsen, Rafael Rum&iacu...
BMVC
2010
14 years 8 months ago
Local Gaussian Processes for Pose Recognition from Noisy Inputs
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
Martin Fergie, Aphrodite Galata