Understanding sprinting motion skills using unsupervised learning for stepwise skill improvements of running motion

Chanjin Seo, Masato Sabanai, Hiroyuki Ogata, Jun Ohya

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

To improve running performances, each runner's skill, such as characteristics and habits, needs to be known, and feedback on the performance should be outputted according to the runner's skill level. In this paper, we propose a new coaching system for detecting the skill of a runner and a method of giving feedback using a sprint motion dataset. Our proposed method calculates an extracted feature to detect the skill using an autoencoder whose middle layer is an LSTM layer; we analyse the feature using hierarchical clustering, and we analyse the human joints that affect the skill. As a result of experiments, five clusters are obtained using hierarchical clustering. This paper clarifies how to detect the skill and to output feedback to achieve a level of performance one step higher than the current level.

本文言語English
ホスト出版物のタイトルICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods
編集者Maria De Marsico, Gabriella Sanniti di Baja, Ana Fred
出版社SciTePress
ページ467-475
ページ数9
ISBN(電子版)9789897583513
DOI
出版ステータスPublished - 2019
イベント8th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2019 - Prague, Czech Republic
継続期間: 2019 2 192019 2 21

出版物シリーズ

名前ICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods

Conference

Conference8th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2019
国/地域Czech Republic
CityPrague
Period19/2/1919/2/21

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識

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