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» Combining Gaussian Mixture Models
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ICIP
2001
IEEE
14 years 10 months ago
Minimum discrimination information clustering: modeling and quantization with Gauss mixtures
Gauss mixtures have gained popularity in statistics and statistical signal processing applications for a variety of reasons, including their ability to well approximatea large cla...
Robert M. Gray, John C. Young, Anuradha K. Aiyer
PRL
2006
153views more  PRL 2006»
13 years 9 months ago
Efficient adaptive density estimation per image pixel for the task of background subtraction
We analyze the computer vision task of pixel-level background subtraction. We present recursive equations that are used to constantly update the parameters of a Gaussian mixture m...
Zoran Zivkovic, Ferdinand van der Heijden
ICASSP
2011
IEEE
13 years 22 days ago
Rapid speaker adaptation with speaker adaptive training and non-negative matrix factorization
In this paper, we describe a novel speaker adaptation algorithm based on Gaussian mixture weight adaptation. A small number of latent speaker vectors are estimated with non-negati...
Xueru Zhang, Kris Demuynck, Hugo Van hamme
ICA
2004
Springer
14 years 2 months ago
Wavelet De-noising for Blind Source Separation in Noisy Mixtures
Blind source separation, which supposes that the sources are independent, is a well known domain in signal processing. However, in a noisy environment the estimation of the criteri...
Bertrand Rivet, Vincent Vigneron, Anisoara Parasch...
ICPR
2006
IEEE
14 years 10 months ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...