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ICCV
2005
IEEE
13 years 10 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 4 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»
12 years 11 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»
13 years 10 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»
14 years 11 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