About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part II

Research Article

Sports Athlete Error Action Recognition System Based on Wireless Communication Network

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-50546-1_25,
        author={Yanlan Huang and Lichun Wang},
        title={Sports Athlete Error Action Recognition System Based on Wireless Communication Network},
        proceedings={Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part II},
        proceedings_a={ADHIP PART 2},
        year={2024},
        month={3},
        keywords={Sports Athletes Standard Action Movement Characteristics Action Recognition Wireless Communication Network Wrong Action},
        doi={10.1007/978-3-031-50546-1_25}
    }
    
  • Yanlan Huang
    Lichun Wang
    Year: 2024
    Sports Athlete Error Action Recognition System Based on Wireless Communication Network
    ADHIP PART 2
    Springer
    DOI: 10.1007/978-3-031-50546-1_25
Yanlan Huang1,*, Lichun Wang1
  • 1: Guangxi College for Preschool Education
*Contact email: hyl5825@163.com

Abstract

Incorrect actions not only affect the training effect, but also cause certain harm to the athlete’s body. A sports athlete incorrect action recognition system based on wireless communication network is proposed. Build a wireless communication network architecture, obtain sports athletes’ sports videos, extract key frames, determine athletes’ positions, extract sports athletes’ action characteristics (STIP characteristics, Cuboids characteristics, enhanced dense trajectory characteristics and covariance characteristics), based on the extraction of sports athletes’ action characteristics, build a Hyperplane based on support vector mechanism, and finally realize the recognition of sports athletes’ wrong actions. The experimental data shows that after the application of the system in this article, the maximum recognition rate of incorrect movements of sports athletes obtained is 96.35%.

Keywords
Sports Athletes Standard Action Movement Characteristics Action Recognition Wireless Communication Network Wrong Action
Published
2024-03-24
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-50546-1_25
Copyright © 2023–2025 ICST
EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL