Special Issue Paper

Grasp synthesis from low-dimensional probabilistic grasp models

  1. Heni Ben Amor*,
  2. Guido Heumer,
  3. Bernhard Jung,
  4. Arnd Vitzthum

Article first published online: 6 AUG 2008

DOI: 10.1002/cav.252

Issue

Computer Animation and Virtual Worlds

Computer Animation and Virtual Worlds

Special Issue: CASA'2008 Special Issue

Volume 19, Issue 3-4, pages 445–454, 2008

Additional Information

How to Cite

Ben Amor, H., Heumer, G., Jung, B. and Vitzthum, A. (2008), Grasp synthesis from low-dimensional probabilistic grasp models. Computer Animation and Virtual Worlds, 19: 445–454. doi: 10.1002/cav.252

Author Information

*VR and Multimedia Group, Institute of Informatics, TU Bergakademie Freiberg, Bernhard-von-Cotta Str. 2, 09599 Freiberg, Germany.

Publication History

  1. Issue published online: 27 AUG 2008
  2. Article first published online: 6 AUG 2008
  3. Manuscript Accepted: 25 JUN 2008
  4. Manuscript Received: 24 JUN 2008

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Keywords:

  • grasp synthesis;
  • principal component analysis;
  • Gaussian mixture models

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.

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