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» Bernoulli Mixture Models for Binary Images
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SADM
2010
141views more  SADM 2010»
12 years 12 months ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman
CORR
2010
Springer
95views Education» more  CORR 2010»
13 years 5 months ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro
CORR
2011
Springer
210views Education» more  CORR 2011»
13 years 2 days ago
Statistical Compressed Sensing of Gaussian Mixture Models
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...
Guoshen Yu, Guillermo Sapiro
ICIP
2008
IEEE
13 years 11 months ago
Multi-object tracking using binary masks
In this paper, we introduce a new method for tracking multiple objects. The method combines Kalman filtering and the Expectation Maximization (EM) algorithm in a novel way to dea...
Sami Huttunen, Janne Heikkilä
CVPR
2009
IEEE
1216views Computer Vision» more  CVPR 2009»
15 years 16 hour ago
Marked Point Processes for Crowd Counting
A Bayesian marked point process (MPP) model is developed to detect and count people in crowded scenes. The model couples a spatial stochastic process governing number and placem...
Robert T. Collins, Weina Ge