Abstract

Annotation and analysis of sports videos is a time consuming task that, once automated, will provide benefits to coaches, players, and spectators. American football, as the most watched sport in the United States, could especially benefit from this automation. Manual annotation and analysis of recorded video of American football games is an inefficient and tedious process. Currently, most college football programs focus on annotating offensive formation. As a first step to further research for this unique application, we use computer vision and deep learning to analyze an overhead image of a football play immediately before the play begins. This analysis consists of locating and labeling individual football players, as well as identifying the formation of the offensive team. We obtain greater than 90% accuracy on both player detection and labeling, and 84.8% accuracy on formation identification. These results prove the feasibility of building a complete American football strategy analysis system using artificial intelligence.

Degree

MS

College and Department

Electrical and Computer Engineering

Rights

https://lib.byu.edu/about/copyright/

Date Submitted

2022-06-29

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd12454

Keywords

computer vision, deep learning, machine learning, sports analysis

Language

english

Included in

Engineering Commons

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