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ICASSP
2011
IEEE
12 years 11 months ago
Gaussian mixture modeling for source localization
Exploiting prior knowledge, we use Bayesian estimation to localize a source heard by a fixed sensor network. The method has two main aspects: Firstly, the probability density fun...
John T. Flåm, Joakim Jalden, Saikat Chatterj...
BMCBI
2008
132views more  BMCBI 2008»
13 years 8 months ago
Mixture models for analysis of melting temperature data
Background: In addition to their use in detecting undesired real-time PCR products, melting temperatures are useful for detecting variations in the desired target sequences. Metho...
Christoffer Nellåker, Fredrik Uhrzander, Joa...
TCSV
2008
177views more  TCSV 2008»
13 years 7 months ago
An ICA Mixture Hidden Markov Model for Video Content Analysis
In this paper, a new theoretical framework based on hidden Markov model (HMM) and independent component analysis (ICA) mixture model is presented for content analysis of video, nam...
Jian Zhou, Xiao-Ping Zhang
ICCV
2009
IEEE
15 years 27 days ago
Deformable Model Fitting with a Mixture of Local Experts
Local experts have been used to great effect for fitting deformable models to images. Typically, the best location in an image for the deformable model’s landmarks are found t...
Jason M. Saragih, Simon Lucey, Jeffrey F. Cohn
ICCV
2005
IEEE
14 years 1 months ago
Bayesian Body Localization Using Mixture of Nonlinear Shape Models
We present a 2D model-based approach to localizing human body in images viewed from arbitrary and unknown angles. The central component is a statistical shape representation of th...
Jiayong Zhang, Robert T. Collins, Yanxi Liu