Exercise recognition system using facial image information from a mobile device

Kaho Kato, Chengshuo Xia, Yuta Sugiura

研究成果: Conference contribution

抄録

Daily exercise has played a significant role for people in staying healthy; however, some people cannot do moderate exercise continuously. In this paper, we proposed an exercise recognition system using facial image information to make daily exercise management convenient. The proposed system gets facial image information from a built-in camera on a mobile device and can recognize nine exercises by a support vector machine’s classifier. When a user faces the camera during the exercise, the system gets time-series data consisting of 62 features on the face. Via leave-one-subject-out cross-validation, the average classification accuracy reached up to 88.2%.

本文言語English
ホスト出版物のタイトルLifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies
出版社Institute of Electrical and Electronics Engineers Inc.
ページ268-272
ページ数5
ISBN(電子版)9781665418751
DOI
出版ステータスPublished - 2021 3 9
イベント3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021 - Nara, Japan
継続期間: 2021 3 92021 3 11

出版物シリーズ

名前LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies

Conference

Conference3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021
国/地域Japan
CityNara
Period21/3/921/3/11

ASJC Scopus subject areas

  • 生体医工学
  • 健康情報学
  • 健康(社会科学)
  • 生化学
  • 人工知能
  • コンピュータ サイエンスの応用

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