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» Learning to Track with Multiple Observers
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MLMI
2007
Springer
14 years 1 months ago
Gaussian Process Latent Variable Models for Human Pose Estimation
We describe a method for recovering 3D human body pose from silhouettes. Our model is based on learning a latent space using the Gaussian Process Latent Variable Model (GP-LVM) [1]...
Carl Henrik Ek, Philip H. S. Torr, Neil D. Lawrenc...
IROS
2009
IEEE
132views Robotics» more  IROS 2009»
14 years 2 months ago
Automatic selection of task spaces for imitation learning
Abstract— Previous work [1] shows that the movement representation in task spaces offers many advantages for learning object-related and goal-directed movement tasks through imit...
Manuel Mühlig, Michael Gienger, Jochen J. Ste...
IROS
2006
IEEE
83views Robotics» more  IROS 2006»
14 years 1 months ago
Using Orthogonal Surface Directions for Autonomous 3D-Exploration of Indoor Environments
— This paper proposes a new tracking algorithm within a 3D-SLAM framework that takes segmented range images as observations. The framework has two layers: the local layer tracks ...
Peter Kohlhepp, Georg Bretthauer, Marcus Walther, ...
CE
2005
170views more  CE 2005»
13 years 7 months ago
Development of an environmental virtual field laboratory
Laboratory exercises, field observations and field trips are a fundamental part of many earth science and environmental science courses. Field observations and field trips can be ...
V. Ramasundaram, S. Grunwald, A. Mangeot, N. B. Co...
NIPS
2007
13 years 9 months ago
Bayes-Adaptive POMDPs
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...