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CVPR
2006
IEEE
14 years 11 months ago
3D People Tracking with Gaussian Process Dynamical Models
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
Raquel Urtasun, David J. Fleet, Pascal Fua
CVPR
2004
IEEE
14 years 11 months ago
Bayesian Assembly of 3D Axially Symmetric Shapes from Fragments
We present a complete system for the purpose of automatically assembling 3D pots given 3D measurements of their fragments commonly called sherds. A Bayesian approach is formulated...
Andrew R. Willis, David B. Cooper
ICIP
2003
IEEE
14 years 10 months ago
A hidden Markov model based framework for recognition of humans from gait sequences
In this paper we propose a generic framework based on Hidden Markov Models (HMMs) for recognition of individuals from their gait. The HMM framework is suitable, because the gait o...
Aravind Sundaresan, Amit K. Roy Chowdhury, Rama Ch...
ECCV
2008
Springer
14 years 11 months ago
A Probabilistic Approach to Integrating Multiple Cues in Visual Tracking
Abstract. This paper presents a novel probabilistic approach to integrating multiple cues in visual tracking. We perform tracking in different cues by interacting processes. Each p...
Wei Du, Justus H. Piater
PVLDB
2008
111views more  PVLDB 2008»
13 years 8 months ago
Approximate lineage for probabilistic databases
In probabilistic databases, lineage is fundamental to both query processing and understanding the data. Current systems s.a. Trio or Mystiq use a complete approach in which the li...
Christopher Ré, Dan Suciu