Automatic Recognition of Offensive Team Formation in American Football Plays
Seminar by Dr. Indriyati Atmosukarto, ADSC Research Scientist
Abstract: American football is the most popular sport in the United States, however game analysis is still done manually. Line of scrimmage and offensive team formation recognition are two statistics that must be tagged by American Football coaches when watching and evaluating past play video clips, a process which takes many man hours per week. These two statistics are also the building blocks for more high-level analysis such as play strategy inference and automatic statistic generation.
Given an American football play clip in our novel framework, we automatically identify the offensive team formation video frame, the line of scrimmage for that play, and the type of player formation the offensive team takes on. The proposed framework achieves 95% accuracy in detecting the formation frame, 98% accuracy in detecting the line of scrimmage, and up to 67% accuracy in classifying the offensive team's formation. We have compiled a dataset comprising more than 800 play-clips of standard and high definition resolution from real-world football games to validate our framework.
Biosketch: Indriyati (Indri) Atmosukarto is a Research Scientist at Advanced Digital Sciences Center (ADSC) in Singapore. Advance Digital Research Center is led by faculty of the University of Illinois at Urbana-Champaign. Indri is currently working on the "Semantic Analysis of Video" project. Their paper was awarded the best paper award at the first IEEE International Workshop on Computer Vision in Sports (CVSports), which was held in conjunction with the IEEE Computer Vision and Pattern Recognition (CVPR) conference, in June.