Automated Swimming Analytics

Swimming Canada is currently working to catch up to rival nations in the areas of data acquisition from race video. To gain a significant competitive intelligence advantage over other nations, Swimming Canada needs a mechanism to gather all necessary analytics quickly, accurately, and efficiently for all athletes in a pool. Recent advances in visual machine learning technology have made it possible to track objects in diverse environments. This project will focus on using these new advances to create a computer system capable of reproducing the current manually captured race analytics. When this is completed, such information can then be passed to the coaches/athletes and utilized to further the development of athletes at a given competition, and in the long term.

Faculty Supervisor:

Ivan Bajic

Student:

Partner:

Own the Podium;Canadian Sport Institute Pacific

Discipline:

Engineering

Sector:

Arts, entertainment and recreation; Health and Related Sciences & Technology; Other services (except public administration); Professional, scientific and technical services; Retail trade

University:

Simon Fraser University

Program:

Accelerate