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Reach out and touch space (motion learning)

Goncalves, Luis and Di Bernardo, Enrico and Perona, Pietro (1998) Reach out and touch space (motion learning). In: Third IEEE International Conference on Automatic Face and Gesture Recognition. IEEE Computer Society , Los Alamitos, CA, pp. 234-239. ISBN 0-8186-8344-9.

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We propose a method for learning models of human motion from a coarsely sampled set of examples. The models we synthesize may be used to generate plausible motions from a high level description consisting of start and stop positions, style, mood, age, etc. In the field of computer vision, such models can be useful for human body motion tracking/estimation and gesture recognition. The models can also be used to generate arbitrary realistic human motion, and may be of help in trying to understand the mechanisms behind the perception of biological motion by the human visual system. Experimental results of the learning technique applied to reaching and drawing motions are presented.

Item Type:Book Section
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Perona, Pietro0000-0002-7583-5809
Additional Information:© 1998 IEEE. Date of Current Version: 06 August 2002. This work is supported in part by the California Institute of Technology; an NSF National Young Investigator Award to P.P.; and the Center for Neuromorphic Systems Engineering as a part of the National Science Foundation Engineering Research Center Program.
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NSF National Young Investigator AwardUNSPECIFIED
NSF Center for Neuromorphic Systems Engineering (CNSE)UNSPECIFIED
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INSPEC Accession Number5920416
Record Number:CaltechAUTHORS:20111221-150812446
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Official Citation:Goncalves, L.; Di Bernardo, E.; Perona, P.; , "Reach out and touch space (motion learning)," Automatic Face and Gesture Recognition, 1998. Proceedings. Third IEEE International Conference on , vol., no., pp.234-239, 14-16 Apr 1998 doi: 10.1109/AFGR.1998.670954 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:28555
Deposited By: Tony Diaz
Deposited On:23 Dec 2011 17:23
Last Modified:09 Nov 2021 16:58

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