Logo image
Back
Analyzing Swimming Performance Using Drone Captured Aerial Videos
Conference proceeding

Analyzing Swimming Performance Using Drone Captured Aerial Videos

Thu Tran, Kenny Tsu Wei Choo, Shaohui Foong, Hitesh Bhardwaj, Shane Kyi Hla Win, Wei Jun Ang, Kenneth Goh, Rajesh Krishna Balan and Assoc Computing Machinery
Proceedings of the 10th Workshop on Micro Aerial Vehicle Networks, Systems, and Applications, pp.7-12
ACM Conferences
MOBISYS '24: The 22nd Annual International Conference on Mobile Systems, Applications and Services
03/06/2024
DOI: https://doi.org/10.1145/3661810.3663464

Abstract

Computing methodologies Computing methodologies -- Artificial intelligence Computing methodologies -- Artificial intelligence -- Computer vision Computing methodologies -- Artificial intelligence -- Computer vision -- Computer vision problems Computing methodologies -- Artificial intelligence -- Computer vision -- Computer vision problems -- Tracking Computing methodologies -- Artificial intelligence -- Computer vision -- Computer vision tasks Computing methodologies -- Artificial intelligence -- Computer vision -- Computer vision tasks -- Scene understanding Computing methodologies -- Artificial intelligence -- Computer vision -- Computer vision tasks -- Vision for robotics Computing methodologies -- Artificial intelligence -- Computer vision -- Image and video acquisition Computing methodologies -- Artificial intelligence -- Computer vision -- Image and video acquisition -- Motion capture Computing methodologies -- Computer graphics Computing methodologies -- Computer graphics -- Animation Computing methodologies -- Computer graphics -- Animation -- Motion capture Computing methodologies -- Computer graphics -- Animation -- Motion processing
Monitoring swimmer performance is crucial for improving training and enhancing athletic techniques. Traditional methods for tracking swimmers, such as above-water and underwater cameras, face limitations due to the need for multiple cameras and obstructions from water splashes. This paper presents a novel approach for tracking swimmers using a moving UAV. The proposed system employs a UAV equipped with a high-resolution camera to capture aerial footage of the swimmers. The footage is then processed using computer vision algorithms to extract the swimmers' positions and movements. This approach offers several advantages, including single camera use and comprehensive coverage. The system's accuracy is evaluated with both training and in competition videos. The results demonstrate the system's ability to accurately track swimmers' movements, limb angles, stroke duration and velocity with the maximum error of 0.3 seconds and 0.35 m/s for stroke duration and velocity, respectively.
url
https://doi.org/10.1145/3661810.3663464View
Published (Version of record) Open

Metrics

1 Record Views

Details

Logo image