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» Learning Articulated Structure and Motion
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ICML
1997
IEEE
14 years 8 months ago
Robot Learning From Demonstration
The goal of robot learning from demonstration is to have a robot learn from watching a demonstration of the task to be performed. In our approach to learning from demonstration th...
Christopher G. Atkeson, Stefan Schaal
ICCV
2007
IEEE
14 years 9 months ago
Graph Based Discriminative Learning for Robust and Efficient Object Tracking
Object tracking is viewed as a two-class 'one-versusrest' classification problem, in which the sample distribution of the target is approximately Gaussian while the back...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
ICML
2007
IEEE
14 years 8 months ago
Hierarchical Gaussian process latent variable models
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
Neil D. Lawrence, Andrew J. Moore
SCIA
2009
Springer
305views Image Analysis» more  SCIA 2009»
14 years 2 months ago
A Convex Approach to Low Rank Matrix Approximation with Missing Data
Many computer vision problems can be formulated as low rank bilinear minimization problems. One reason for the success of these problems is that they can be efficiently solved usin...
Carl Olsson, Magnus Oskarsson
CAD
2006
Springer
13 years 7 months ago
An efficient, error-bounded approximation algorithm for simulating quasi-statics of complex linkages
Design and analysis of articulated mechanical structures, commonly referred to as linkages, is an integral part of any CAD/CAM system. The most common approaches formulate the pro...
Stephane Redon, Ming C. Lin