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PCM
2004
Springer
168views Multimedia» more  PCM 2004»
14 years 20 days ago
Approximating Inference on Complex Motion Models Using Multi-model Particle Filter
Abstract. Due to its great ability of conquering clutters, which is especially useful for high-dimensional tracking problems, particle filter becomes popular in the visual trackin...
Jianyu Wang, Debin Zhao, Shiguang Shan, Wen Gao
AMDO
2008
Springer
13 years 9 months ago
Exploiting Structural Hierarchy in Articulated Objects Towards Robust Motion Capture
This paper presents a general analysis framework towards exploiting the underlying hierarchical and scalable structure of an articulated object for pose estimation and tracking. Th...
Cristian Canton-Ferrer, Josep R. Casas, Montse Par...
AUTOMATICA
2008
92views more  AUTOMATICA 2008»
13 years 7 months ago
Box particle filtering for nonlinear state estimation using interval analysis
In recent years particle ...lters have been applied to a variety of state estimation problems. A particle ...lter is a sequential Monte Carlo Bayesian estimator of the posterior d...
Fahed Abdallah, Amadou Gning, Philippe Bonnifait
PAMI
2006
159views more  PAMI 2006»
13 years 7 months ago
Consistency Checks for Particle Filters
An "inconsistent" particle filter produces--in a statistical sense--larger estimation errors than predicted by the model on which the filter is based. Two test variables ...
Ferdinand van der Heijden
ICCV
2001
IEEE
14 years 9 months ago
People Tracking Using Hybrid Monte Carlo Filtering
Particle filters are used for hidden state estimation with nonlinear dynamical systems. The inference of 3-d human motion is a natural application, given the nonlinear dynamics of...
Kiam Choo, David J. Fleet