Normal/abnormal gait analysis based on the statistical registration and modeling of the frontal view gait data

Kosuke Okusa, Toshinari Kamakura

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

2 被引用数 (Scopus)

抄録

We study the problem of analyzing and classifying frontal view gait video data. In this study, we suppose that frontal view gait data as a mixing of scale changing, human movements and speed changing parameters. We estimate these parameters using the statistical registration and modeling on a video data. Our gait model is based on human gait structure and temporal-spatial relations between camera and subject. To demonstrate the effectiveness of our method, we conducted two sets of experiments, assessing the proposed method in gait analysis for young/elderly person and abnormal gait detection. In abnormal gait detection experiment, we apply K-nearestneighbor classifier, using the estimated parameters, to perform normal/abnormal gait detect, and present results from an experiment involving 120 subjects (young person), and 60 subjects (elderly person). As a result, our method shows high detection rate.

本文言語英語
ホスト出版物のタイトルInternational MultiConference of Engineers and Computer Scientists, IMECS 2012
編集者Jon Burgstone, S. I. Ao, Craig Douglas, W. S. Grundfest
出版社Newswood Limited
ページ443-448
ページ数6
ISBN(電子版)9789881925169
ISBN(印刷版)9789881925114
出版ステータス出版済み - 1 1 2012
外部発表はい
イベント2012 World Congress on Engineering and Computer Science, WCECS 2012 - San Francisco, 米国
継続期間: 10 24 201210 26 2012

出版物シリーズ

名前Lecture Notes in Engineering and Computer Science
1
ISSN(印刷版)2078-0958

その他

その他2012 World Congress on Engineering and Computer Science, WCECS 2012
Country米国
CitySan Francisco
Period10/24/1210/26/12

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)

フィンガープリント 「Normal/abnormal gait analysis based on the statistical registration and modeling of the frontal view gait data」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル