Smart Badminton Detection System Based on Scaled-YOLOv4

Yen Ting Chen, Jar Ferr Yang, Kuo Cheng Tu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In recent years, artificial intelligence applied to computer vision is growing popularly. Also, the smart sport system is now a flourishing research topic that more and more researchers are studying in this area. In this paper, we used scaled-YOLOv4 [1], which is now the state-of-the-art deep learning model on object detection, as our deep learning network to build a smart badminton detection system. We proposed the modified scaled-YOLOv4 by adding residual attention modules to detect the positions of badminton players and the shuttlecock and an image projection method to calculate the moving distance of the players.

Original languageEnglish
Title of host publicationISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems
Subtitle of host publication5G Dream to Reality, Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665419512
DOIs
Publication statusPublished - 2021
Event2021 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2021 - Hualien, Taiwan
Duration: 2021 Nov 162021 Nov 19

Publication series

NameISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems: 5G Dream to Reality, Proceeding

Conference

Conference2021 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2021
Country/TerritoryTaiwan
CityHualien
Period21-11-1621-11-19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing
  • Safety, Risk, Reliability and Quality

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