System and method for player reidentification in broadcast video

Abstract

A system and method of re-identifying players in a broadcast video feed are provided herein. A computing system retrieves a broadcast video feed for a sporting event. The broadcast video feed includes a plurality of video frames. The computing system generates a plurality of tracks based on the plurality of video frames. Each track includes a plurality of image patches associated with at least one player. Each image patch of the plurality of image patches is a subset of the corresponding frame of the plurality of video frames. For each track, the computing system generates a gallery of image patches. A jersey number of each player is visible in each image patch of the gallery. The computing system matches, via a convolutional autoencoder, tracks across galleries. The computing system measures, via a neural network, a similarity score for each matched track and associates two tracks based on the measured similarity.

Description

[0001] priority document [0002] This application claims the priority of the U.S. provisional application with the filing date of February 28, 2019 and the application number US 62 / 811,889, the entire contents of which are incorporated herein by reference. technical field [0003] The present disclosure generally relates to systems and methods for player re-identification in broadcast video. Background technique [0004] Player tracking data has been used in many sports for team and player analysis over the years. However, conventional player tracking systems require sports analytics companies to install fixed cameras at each field where a team plays. This constraint limits the scalability of the athlete tracking system, with limited data collection for current competitions. Additionally, such constraints can incur significant expense for sports analysis companies due to the costs associated with installing the necessary field hardware and maintaining such hardware. Con...

AI Technical Summary

Problems solved by technology

However, conventional player tracking systems require sports analytics companies to install fixed cameras at each field where a team plays

This constraint limits the scalability of the athlete tracking system, with limited data collection for current competitions

Additionally, such constraints can incur significant expenses for sports analytics companies due to the costs associated with installing the necessary field hardware and maintaining such hardware

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