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JACIII Vol.15 No.8 pp. 1011-1018
doi: 10.20965/jaciii.2011.p1011
(2011)

Paper:

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Acquisition of Embodied Knowledge on Gesture Motion by Singular Value Decomposition

Isao Hayashi*, Yinlai Jiang**, and Shuoyu Wang**

*Graduate School of Informatics, Kansai University, 2-1-1 Ryozenji-cho, Takatsuki, Osaka 569-1095, Japan

**School of Systems Engineering, Kochi University of Technology, 185 Miyanokuti, Tosayamada, Kami, Kochi 782-8502, Japan

Received:
March 10, 2011
Accepted:
July 15, 2011
Published:
October 20, 2011
Creative Commons License
Keywords:
human embodied knowledge, skill acquisition, motion recognition, singular value decomposition
Abstract
Communication is classified in terms of verbal and nonverbal information. We discuss an acquisition method of knowledge from nonverbal information. In particular, a gesture is an efficient form of nonverbal communication as well as in verbal ways, and we formulate here a method that measures similarity and estimation between gestures. A gesture includes human embodied knowledge, and therefore the visible bodily actions can communicate particular messages. However, we have infinite patterns for gesture, determined by personality. Recently, the singular spectrum analysis method is utilized as an attractive method. In this paper, we propose a new method for acquiring embodied knowledge from time-series data on gestures using singular value decomposition. The motion behavior is categorized into several clusters with similarity and estimation between interval time-series data. We discuss the usefulness of the proposed method using an example of gesture motion.
Cite this article as:
I. Hayashi, Y. Jiang, and S. Wang, “Acquisition of Embodied Knowledge on Gesture Motion by Singular Value Decomposition,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.8, pp. 1011-1018, 2011.
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