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.
|出版狀態||Published - 18 9月 2019|
|事件||20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019 - Matsue, Japan|
持續時間: 18 9月 2019 → 20 9月 2019
|Conference||20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019|
|期間||18/09/19 → 20/09/19|