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

07/12/2019
by   Tzu-Han Hsu, et al.
0

Computer vision based object tracking has been used to annotate and augment sports video. For sports learning and training, video replay is often used in post-match review and training review for tactical analysis and movement analysis. For automatically and systematically competition data collection and tactical analysis, a project called CoachAI has been supported by the Ministry of Science and Technology, Taiwan. 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 a tactical analysis. To reveal data in more understandable forms and to help in pre-match training, AR/VR techniques will be used to visualize data, tactics, and so on. 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.

READ FULL TEXT
research
07/29/2023

Automated Hit-frame Detection for Badminton Match Analysis

Sports professionals constantly under pressure to perform at the highest...
research
08/22/2022

Survey of Machine Learning Techniques To Predict Heartbeat Arrhythmias

Many works in biomedical computer science research use machine learning ...
research
07/24/2023

VIRD: Immersive Match Video Analysis for High-Performance Badminton Coaching

Badminton is a fast-paced sport that requires a strategic combination of...
research
09/07/2016

Tracking Algorithm for Microscopic Flow Data Collection

Various methods to automate traffic data collection have recently been d...
research
08/18/2023

Surprise machines: revealing Harvard Art Museums' image collection

Surprise Machines is a project of experimental museology that sets out t...
research
05/19/2022

Real Time Multi-Object Detection for Helmet Safety

The National Football League and Amazon Web Services teamed up to develo...
research
01/07/2021

On the Management of Type 1 Diabetes Mellitus with IoT Devices and ML Techniques

The purpose of this Conference is to present the main lines of base proj...

Please sign up or login with your details

Forgot password? Click here to reset