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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
CSDA
2007
126views more  CSDA 2007»
13 years 7 months ago
A consistent nonparametric Bayesian procedure for estimating autoregressive conditional densities
This article proposes a Bayesian infinite mixture model for the estimation of the conditional density of an ergodic time series. A nonparametric prior on the conditional density ...
Yongqiang Tang, Subhashis Ghosal
TMI
2010
175views more  TMI 2010»
13 years 2 months ago
Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Thomas Vincent, Laurent Risser, Philippe Ciuciu
FGR
2006
IEEE
148views Biometrics» more  FGR 2006»
14 years 1 months ago
Gait Tracking and Recognition Using Person-Dependent Dynamic Shape Model
Characteristics of the 2D shape deformation in human motion contain rich information for human identification and pose estimation. In this paper, we introduce a framework for sim...
Chan-Su Lee, Ahmed M. Elgammal
CVPR
2009
IEEE
1216views Computer Vision» more  CVPR 2009»
15 years 2 months 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