Computer Vision / Video Analytics

Deep Learning May Soon Assist Pro Football Coaches

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  • Oregon State University professor Alan Fern is training a GPU-accelerated neural network to understand and coach football.
  • The model was trained using CUDA, Tesla K80 GPUs, and cuDNN versions of Caffe and Torch deep learning frameworks on video of Oregon State football plays and hundreds of hours of high school football.
  • The algorithm detects the snap, distinguishes between kicking, passing and running plays, and identifies whether a team is on offense or defense.
  • Fern hopes the system will enable coaches, analysts and fans to query football video libraries for indexing, statistics and player-contribution analysis.

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An Oregon State University professor is training his GPU-accelerated neural network to understand and coach football.

“AI will revolutionize sports,” said Alan Fern, lead researcher and computer science professor at Oregon State University.

Using CUDA, Tesla K80 GPUs, and the cuDNN versions of Caffe and Torch deep learning frameworks, Fern trained his model on video of Oregon State football plays and hundreds of hours of high school football to detect the snap, the difference between kicking, passing and running plays, and whether a team is on offense or defense.

With this knowledge, Fern is hoping the algorithm will allow coaches, analysts, and fans to easily pose queries against libraries of football video for indexing and collecting statistics, such as a head coach being able to see the best matchups between receivers and cornerbacks or to measure the contribution of each player to every play.

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