Journal of Information Processing
Online ISSN : 1882-6652
ISSN-L : 1882-6652
Low-dimensional Feature Vector Extraction from Motion Capture Data by Phase Plane Analysis
Takeshi MiuraTakaaki KaigaTakeshi ShibataKatsubumi TajimaHideo Tamamoto
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JOURNAL FREE ACCESS

2017 Volume 25 Pages 884-887

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Abstract

This paper proposes a method to obtain a low-dimensional feature vector appropriately representing the characteristics of a given motion-capture data stream. The feature vector is derived based on the concept of phase plane analysis. A set of phase plane trajectories are obtained from the temporal variation of the state variables representing the body-segment arrangement. The information on six motion-characteristic properties is extracted from the shapes of the trajectories, and used as the components of a six-dimensional feature vector. The experimental results showed the effectiveness and limitation of the proposed method.

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© 2017 by the Information Processing Society of Japan
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