CoachAI: A Project for Microscopic Badminton Match Data Collection and Tactical Analysis

Tzu Han Hsu, Ching Hsuan Chen, Nyan Ping Jut, Tsi-Ui Ik*, Wen-Chih Peng, Chih-Chuan Wang, Yuan Hsiang Lin, Yu-Shuen Wang, Yu-Chee Tsengt, Jiun-Long Huang, Yu-Tai Ching

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Computer vision based object tracking has been used to annotate and augment sports video. For automatically and systematically competition data collection and tactical analysis. The proposed project also includes research of data visualization, connected training auxiliary devices, and data warehouse. Deep learning techniques will be used to develop video-based real-time microscopic competition data collection based on broadcast competition video. Machine learning techniques will be used to develop tactical analysis. In addition, training auxiliary devices including smart badminton rackets and connected serving machines will be developed based on the IoT technology to further utilize competition data and tactical data and boost training efficiency. Especially, the connected serving machines will be developed to perform specified tactics and to interact with players in their training.

Original languageEnglish
Title of host publication2019 20th Asia-Pacific Network Operations and Management Symposium
Subtitle of host publicationManagement in a Cyber-Physical World, APNOMS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9784885523205
DOIs
StatePublished - Sep 2019
Event20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019 - Matsue, Japan
Duration: 18 Sep 201920 Sep 2019

Publication series

Name2019 20th Asia-Pacific Network Operations and Management Symposium: Management in a Cyber-Physical World, APNOMS 2019

Conference

Conference20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019
CountryJapan
CityMatsue
Period18/09/1920/09/19

Keywords

  • cloud service
  • competition data collection
  • computer vision
  • deep learning
  • OpenPose
  • smart racket
  • tactical analysis
  • TrackNet
  • YOLOv3

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