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JAIR
1998
198views more  JAIR 1998»
13 years 5 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
ICML
2008
IEEE
14 years 6 months ago
Estimating local optimums in EM algorithm over Gaussian mixture model
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is no...
Zhenjie Zhang, Bing Tian Dai, Anthony K. H. Tung
PAMI
2007
253views more  PAMI 2007»
13 years 5 months ago
Gaussian Mean-Shift Is an EM Algorithm
The mean-shift algorithm, based on ideas proposed by Fukunaga and Hostetler (1975), is a hill-climbing algorithm on the density defined by a finite mixture or a kernel density e...
Miguel Á. Carreira-Perpiñán
ESANN
2003
13 years 7 months ago
On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures
Efficient probability density function estimation is of primary interest in statistics. A popular approach for achieving this is the use of finite Gaussian mixture models. Based on...
Cédric Archambeau, John Aldo Lee, Michel Ve...
PRL
2006
153views more  PRL 2006»
13 years 5 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