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  3. RUEFER: Revolutionary Unsupervised Engine for Football Event Reporting RUEFER: Revolutionary Unsupervised Engine for Football Event Reporting

RUEFER: Revolutionary Unsupervised Engine for Football Event Reporting

Did you ever want your favourite TV commentator to comment the football game of your favourite team in the third Swiss League as super fan? With this project, this should soon be possible.

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

13.06.2023 - 31.12.2024

Overview

Digital augmented video streams are becoming increasingly important in the world of sports. Applications like VAR (Video Assistant Referee) in football, digital line judges in tennis, analysis of player movements and tactical positioning in sports studios or as part of competition preparation, and the display of optimal racing lines in skiing or motorsports are already commonplace in the sports industry. With technological advancements, the required equipment for recording raw video data is becoming more affordable, making entry into video streaming more accessible, especially for less popular sports and smaller clubs.

Meanwhile, videos of tournaments or competitions from almost all sports can be accessed online. However, this doesn't automatically mean that they are consumed. The democratization of sports aims to make a greater diversity of sports, including those at lower performance levels, accessible to a lay audience. One fundamental requirement for the attractiveness of such content is its presentation in the form of commentary, reports, and background stories.

The goal of this project is to employ state-of-the-art AI technology to overlay a video stream of a sports event with live commentary and digitally generate speech, all tailored to the preferences of the viewers. Imagine being able to have the football match of your local favorite team in the third Swiss league commented on by Rainer-Maria Salzgeber, as if he were a superfan. With our technology, this should become possible.

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Facts

Type of project

Forschung

Internal organisations involved
  • Algorithmic Business DL
External project funder
  • Stiftung für Innovation und technische Ausbildung (SITA)
Funding
  • Private / Stiftungen
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Persons involved: internal

Project manager
  • Thomas Koller
Member of project team
  • Marc Pouly
  • Cyril Winkler
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Persons involved: external

External member of project team
  • Solange Emmenegger

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

06/13/2023 - 12/31/2024

Project Head

Prof. Dr. Thomas Koller

Head of the Master's Program in Engineering

+41 41 757 68 32

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Lucerne University of Applied Sciences and Arts


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info@hslu.ch

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