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PCM
2004
Springer
168views Multimedia» more  PCM 2004»
15 years 2 months 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
14 years 11 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»
14 years 9 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»
14 years 9 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
15 years 11 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