2020/01/13 by Timothy Woinoski, Woinoski, Timothy, Alon Harell +4
Computer Science · Engineering · Environmental Science · #Analytics #Anomaly Detection Techniques and Applications #Artificial intelligence #Cartography #Computer Vision and Pattern Recognition (cs.CV) #Computer science #Data analysis #Data collection #Data mining #Data science #Engineering #FOS: Computer and information sciences #Geography #Human Pose and Action Recognition #Scale (ratio) #Tracking (education) #Water Quality Monitoring Technologies #Work (physics) #cs.CV
paper · pdf · doi:10.48550/arxiv.2001.04433
arxiv created 2020/01/13 · openalex publication_date 2020/01/13 · arxiv updated 2020/01/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Methods for creating a system to automate the collection of swimming analytics on a pool-wide scale are considered in this paper. There has not been much work on swimmer tracking or the creation of a swimmer database for machine learning purposes. Consequently, methods for collecting swimmer data from videos of swim competitions are explored and analyzed. The result is a guide to the creation of a comprehensive collection of swimming data suitable for training swimmer detection and tracking systems. With this database in place, systems can then be created to automate the collection of swimming analytics.