Towards Automated Swimming Analytics Using Deep Neural Networks

• URL: http://arxiv.org/abs/2001.04433v1
• Date: Mon, 13 Jan 2020 18:06:53 GMT
• Title: Towards Automated Swimming Analytics Using Deep Neural Networks
• Authors: Timothy Woinoski and Alon Harell and Ivan V. Bajic
• Abstract summary: Methods for creating a system to automate the collection of swimming analytics are considered in this paper. The result is a guide to the creation of a comprehensive collection of swimming data suitable for training swimmer detection and tracking systems.
• Score: 28.167294398293297
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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