Grasp synthesis from low-dimensional probabilistic grasp models

Authors:
Heni Ben Amor;Guido Heumer;Bernhard Jung;Arnd Vitzthum
Affiliations:
(Correspd.) VR and Multimedia Group, Institute of Informatics, TU Bergakademie Freiberg, Bernhard-von-Cotta Str. 2, 09599 Freiberg, Germany.;-;-;-
Venue:
Computer Animation and Virtual Worlds - CASA'2008 Special Issue
Year:
2008

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Abstract

We propose a novel data-driven animation method for the synthesis of natural looking human grasping. Motion data captured from human grasp actions is used to train a probabilistic model of the human grasp space. This model greatly reduces the high number of degrees of freedom of the human hand to a few dimensions in a continuous grasp space. The low dimensionality of the grasp space in turn allows for efficient optimization when synthesizing grasps for arbitrary objects. The method requires only a short training phase with no need for preprocessing of graphical objects for which grasps are to be synthesized. Copyright © 2008 John Wiley & Sons, Ltd.