Individual Action and Group Activity Recognition in Soccer Videos from a Static Panoramic Camera

Beerend Gerats, Beerend Gerats, Henri Bouma, Wouter Uijens, Gwenn Englebienne, Luuk Spreeuwers

2021

Abstract

Data and statistics are key to soccer analytics and have important roles in player evaluation and fan engagement. Automatic recognition of soccer events - such as passes and corners - would ease the data gathering process, potentially opening up the market for soccer analytics at non professional clubs. Existing approaches extract events on group level only and rely on television broadcasts or recordings from multiple camera viewpoints. We propose a novel method for the recognition of individual actions and group activities in panoramic videos from a single viewpoint. Three key contributions in the proposed method are (1) player snippets as model input, (2) independent extraction of spatio-temporal features per player, and (3) feature contextualisation using zero-padding and feature suppression in graph attention networks. Our method classifies video samples in eight action and eleven activity types, and reaches accuracies above 75% for ten of these classes.

Paper Citation

in Harvard Style

Gerats B., Bouma H., Uijens W., Englebienne G. and Spreeuwers L. (2021). Individual Action and Group Activity Recognition in Soccer Videos from a Static Panoramic Camera.In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-486-2, pages 594-601. DOI: 10.5220/0010303505940601

in Bibtex Style

@conference{icpram21,
author={Beerend Gerats and Henri Bouma and Wouter Uijens and Gwenn Englebienne and Luuk Spreeuwers},
title={Individual Action and Group Activity Recognition in Soccer Videos from a Static Panoramic Camera},
booktitle={Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2021},
pages={594-601},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010303505940601},
isbn={978-989-758-486-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Individual Action and Group Activity Recognition in Soccer Videos from a Static Panoramic Camera
SN - 978-989-758-486-2
AU - Gerats B.
AU - Bouma H.
AU - Uijens W.
AU - Englebienne G.
AU - Spreeuwers L.
PY - 2021
SP - 594
EP - 601
DO - 10.5220/0010303505940601