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ICRA
2007
IEEE
160views Robotics» more  ICRA 2007»
14 years 3 months ago
CRF-Filters: Discriminative Particle Filters for Sequential State Estimation
Abstract— Particle filters have been applied with great success to various state estimation problems in robotics. However, particle filters often require extensive parameter tw...
Benson Limketkai, Dieter Fox, Lin Liao
AUTOMATICA
2008
92views more  AUTOMATICA 2008»
13 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
SAC
2008
ACM
13 years 8 months ago
Adaptive methods for sequential importance sampling with application to state space models
Abstract. In this paper we discuss new adaptive proposal strategies for sequential Monte Carlo algorithms--also known as particle filters--relying on new criteria evaluating the qu...
Julien Cornebise, Eric Moulines, Jimmy Olsson
CVPR
2008
IEEE
14 years 11 months ago
Sequential particle swarm optimization for visual tracking
Visual tracking usually involves an optimization process for estimating the motion of an object from measured images in a video sequence. In this paper, a new evolutionary approac...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
ICIP
2005
IEEE
14 years 11 months ago
Visual tracking using sequential importance sampling with a state partition technique
Sequential importance sampling (SIS), also known as particle filtering, has drawn increasing attention recently due to its superior performance in nonlinear and non-Gaussian dynam...
Yan Zhai, Mark B. Yeary, Joseph P. Havlicek, Jean-...