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» Sparse Representation for Gaussian Process Models
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ICASSP
2011
IEEE
12 years 11 months ago
Discriminant binary data representation for speaker recognition
In supervector UBM/GMM paradigm, each acoustic file is represented by the mean parameters of a GMM model. This supervector space is used as a data representation space, which has...
Jean-François Bonastre, Pierre-Michel Bousq...
ICML
2010
IEEE
13 years 8 months ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...
ICIP
1998
IEEE
14 years 9 months ago
Image Sequence Analysis and Segmentation using G-blobs
This paper introduces a new generalisation of the familiar scale-space and wavelet representations, designed specifically to deal with the complexities of representing motions ind...
Andrew Calway, Peter Meulemans, Roland G. Wilson, ...
CGF
2005
186views more  CGF 2005»
13 years 7 months ago
Interpolatory Refinement for Real-Time Processing of Point-Based Geometry
The point set is a flexible surface representation suitable for both geometry processing and real-time rendering. In most applications, the control of the point cloud density is c...
Gaël Guennebaud, Loïc Barthe, Mathias Pa...
WACV
2008
IEEE
14 years 1 months ago
Background Subtraction for Temporally Irregular Dynamic Textures
In the traditional mixture of Gaussians background model, the generating process of each pixel is modeled as a mixture of Gaussians over color. Unfortunately, this model performs ...
Gerald Dalley, Joshua Migdal, W. Eric L. Grimson