Automated Clipping of Soccer Events using Machine Learning

Extracting highlight clips from soccer matches requires tedious, time-consuming, and expensive manual labor. Human operators need to search for appropriate clipping points and trim away the unwanted scenes. In our work, we aim for an automated process for generating event highlights. In particular, we develop AI-models for scene boundary detection and logo detection. Using different datasets, we present two models that automatically find the appropriate time interval for goal event extraction. The models are evaluated quantitatively, and the results show that we find the logo and scene shifts with high accuracy. Our event clipping methodology is a potential building block for a larger, fully-automated sports broadcast production pipeline.