Low-dimensional Feature Vector Extraction from Motion Capture Data by Phase Plane Analysis

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 v...

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Bibliographic Details
Published inJournal of Information Processing Vol. 25; pp. 884 - 887
Main Authors Miura, Takeshi, Kaiga, Takaaki, Shibata, Takeshi, Tajima, Katsubumi, Tamamoto, Hideo
Format Journal Article
LanguageEnglish
Published Tokyo Information Processing Society of Japan 01.01.2017
Japan Science and Technology Agency
Subjects
Data encryption
Feature extraction
feature vector
Motion capture
motion characteristic
phase plane analysis
Public Key Infrastructure
Trajectory analysis
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Summary: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.
ISSN:1882-6652
1882-6652
DOI:10.2197/ipsjjip.25.884