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arXiv · 2001.04433

Towards Automated Swimming Analytics Using Deep Neural Networks

Timothy Woinoski·Alon Harell·Ivan V. Bajic
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Abstract

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.

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Timothy Woinoski, Alon Harell, Ivan V. Bajic. 2020-01-13. Towards Automated Swimming Analytics Using Deep Neural Networks. https://arxiv.org/abs/2001.04433

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