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» Simplifying Mixture Models Using the Unscented Transform
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PAMI
2008
140views more  PAMI 2008»
13 years 4 months ago
Simplifying Mixture Models Using the Unscented Transform
Mixture of Gaussians (MoG) model is a useful tool in statistical learning. In many learning processes that are based on mixture models, computational requirements are very demandin...
Jacob Goldberger, Hayit Greenspan, Jeremie Dreyfus...
ICASSP
2009
IEEE
13 years 11 months ago
People location and orientation tracking in multiple views
This paper presents a multi-view approach to the tracking of people location and orientation. To achieve efficient and accurate likelihood evaluation, a novel likelihood computat...
Huan Jin, Gang Qian
INTERSPEECH
2010
12 years 11 months ago
Unscented transform with online distortion estimation for HMM adaptation
In this paper, we propose to improve our previously developed method for joint compensation of additive and convolutive distortions (JAC) applied to model adaptation. The improvem...
Jinyu Li, Dong Yu, Yifan Gong, L. Deng
IPMI
2009
Springer
14 years 5 months ago
Neural Tractography Using An Unscented Kalman Filter
We describe a technique to simultaneously estimate a local neural fiber model and trace out its path. Existing techniques estimate the local fiber orientation at each voxel indepen...
James G. Malcolm, Martha Elizabeth Shenton, Yogesh...
IVC
2010
128views more  IVC 2010»
13 years 2 months ago
Online kernel density estimation for interactive learning
In this paper we propose a Gaussian-kernel-based online kernel density estimation which can be used for applications of online probability density estimation and online learning. ...
Matej Kristan, Danijel Skocaj, Ales Leonardis