Computer Vision 360 Video Analysis in Sports: 3D Athlete Pose and Rig Motion Estimation in Olympic Sailing
Year: 2026
Type: article
Abstract: This paper presents a novel system for estimating 3D athlete pose, boom angle, and rudder angle in Olympic dinghy sailing using onboard 360° video footage. The proposed approach integrates adaptive panorama slicing, keypoint-based rig detection, and geometric ray-casting into an end-to-end pipeline for quantitative performance analysis under real-world on-water conditions. Traditionally, restrictive International Laser Class Association (ILCA) rules have prohibited advanced sensor systems during competition. However, recent rule changes permit a single onboard camera, enabling unobtrusive and rule-compliant measurement solutions. The purpose of this study is to evaluate whether a competition-legal 360° camera combined with computer vision can provide meaningful performance-related measurements in Olympic sailing. The experimental results indicate that computer-vision-based analysis can complement traditional performance assessment and provide access to data previously limited to physical sensors or manual estimation. The system can support teams and coaches in identifying technique-related performance opportunities.
Source: Applied Sciences
DOI: 10.3390/app16031386
Institution: Norwegian University of Science and Technology
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7126078155
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