Grasp synthesis from low‐dimensional probabilistic grasp models | Zendy

Ben Amor Heni | Zendy; Heumer Guido | Zendy; Jung Bernhard | Zendy; Vitzthum Arnd | Zendy

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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.

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