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Grasp synthesis from low‐dimensional probabilistic grasp models
Author(s) -
Ben Amor Heni,
Heumer Guido,
Jung Bernhard,
Vitzthum Arnd
Publication year - 2008
Publication title -
computer animation and virtual worlds
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 49
eISSN - 1546-427X
pISSN - 1546-4261
DOI - 10.1002/cav.252
Subject(s) - grasp , computer science , probabilistic logic , animation , preprocessor , artificial intelligence , curse of dimensionality , space (punctuation) , computer vision , computer graphics (images) , programming language , operating system
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.