PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Regression-based Hand Pose Estimation from Multiple Cameras
Teo de Campos and David Murray
In: CVPR - IEEE International Conference on Computer Vision and Pattern Recognition, 17-22 June 2006, New York.

Abstract

The RVM-based learning method for whole body pose estimation proposed by Agarwal and Triggs is adapted to hand pose recovery. To help overcome the difficulties presented by the greater degree of self-occlusion and the wider range of poses exhibited in hand imagery, the adaptation proposes a method for combining multiple views. Comparisons of performance using single versus multiple views are reported for both synthesized and real imagery, and the effects of the number of image measurements and the number of training samples on performance are explored.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:9139
Deposited By:Teo de Campos
Deposited On:21 February 2012