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SAC
2008
ACM
13 years 4 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
ICCV
2001
IEEE
14 years 6 months ago
3D Object Tracking Using Shape-Encoded Particle Propagation
We present a comprehensive treatment of 3D object tracking by posing it as a nonlinear state estimation problem. The measurements are derived using the outputs of shape-encoded fi...
Hankyu Moon, Rama Chellappa, Azriel Rosenfeld
ICPR
2006
IEEE
14 years 6 months ago
Real-Time 3D Articulated Pose Tracking using Particle Filters Interacting through Belief Propagation
This article proposes a new statistical model for fast 3D articulated body tracking, similar to the loose-limbed model, but where inter-frame coherence is taken into account by us...
Olivier Bernier
ATAL
2005
Springer
13 years 10 months ago
Approximating state estimation in multiagent settings using particle filters
State estimation consists of updating an agent’s belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalize...
Prashant Doshi, Piotr J. Gmytrasiewicz
CVIU
2007
154views more  CVIU 2007»
13 years 4 months ago
Smart particle filtering for high-dimensional tracking
Tracking articulated structures like a hand or body within a reasonable time is challenging because of the high dimensionality of the state space. Recently, a new optimization met...
Matthieu Bray, Esther Koller-Meier, Luc J. Van Goo...