Player Identification in Different Sports

Ahmed Nady, Elsayed E. Hemayed, Elsayed E. Hemayed

2021

Abstract

Identifying players through jersey numbers in sports videos is a challenging task. Jersey number can be distorted and deformed due to variation of the player’s posture and the camera’s view. Moreover, it varies in font and size due to the different sports fields. In this paper, we present a deep learning-based framework to address these challenges of jersey number recognition. Our framework has three main parts. Firstly, it detects players on the court using state of the art object detector YOLO V4. Secondly, each jersey number per detected player bounding boxes is localized. Then a four-stage scene text recognition is employed for recognizing detected number regions. A benchmark dataset consists of three subsets is collected. Two subsets include player images from different fields in basketball sport and the third includes player images from ice hockey sport. Experiments show that the proposed approach is effective compared to state-of-the-art jersey number recognition methods. This research makes the automation of player identification applicable across several sports.

Paper Citation

in Harvard Style

Nady A. and Hemayed E. (2021). Player Identification in Different Sports. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP; ISBN 978-989-758-488-6, SciTePress, pages 653-660. DOI: 10.5220/0010341706530660

in Bibtex Style

@conference{visapp21,
author={Ahmed Nady and Elsayed E. Hemayed},
title={Player Identification in Different Sports},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP},
year={2021},
pages={653-660},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010341706530660},
isbn={978-989-758-488-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP
TI - Player Identification in Different Sports
SN - 978-989-758-488-6
AU - Nady A.
AU - Hemayed E.
PY - 2021
SP - 653
EP - 660
DO - 10.5220/0010341706530660
PB - SciTePress