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CIRA
2007
IEEE
179views Robotics» more  CIRA 2007»
13 years 10 months ago
Learning Tactic-Based Motion Models of a Moving Object with Particle Filtering
— Learning motion models of a moving object is a challenge for autonomous robots. We address the particular instance of parameter learning when tracking object motions in a switc...
Yang Gu, Manuela M. Veloso
ICRA
2008
IEEE
155views Robotics» more  ICRA 2008»
13 years 10 months ago
Learning tactic-based motion models with fast particle smoothing
— Learning parameters of a motion model is an important challenge for autonomous robots. We address the particular instance of parameter learning when tracking motions with a swi...
Yang Gu, Manuela M. Veloso
ICML
2006
IEEE
14 years 4 months ago
Fast particle smoothing: if I had a million particles
We propose efficient particle smoothing methods for generalized state-spaces models. Particle smoothing is an expensive O(N2 ) algorithm, where N is the number of particles. We ov...
Mike Klaas, Mark Briers, Nando de Freitas, Arnaud ...
ICRA
2009
IEEE
163views Robotics» more  ICRA 2009»
13 years 10 months ago
Markerless human motion tracking with a flexible model and appearance learning
— A new approach to the 3D human motion tracking problem is proposed, which combines several particle filters with a physical simulation of a flexible body model. The flexible...
Florian Hecht, Pedram Azad, Rüdiger Dillmann
ICIP
2007
IEEE
14 years 5 months ago
3D Human Motion Tracking using Manifold Learning
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Feng Guo, Gang Qian