Towards Automated Swimming Analytics Using Deep Neural Networks
This addresses the lack of automated analytics for swimming competitions, but it is incremental as it focuses on data collection rather than novel analytics.
The paper tackled the problem of automating swimming analytics by exploring methods to collect swimmer data from competition videos, resulting in a guide for creating a comprehensive database suitable for training detection and tracking systems.
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.