Tracking Data Visual Representations for Sports Broadcasting Enrichment

Murilo Couceiro, Murilo Couceiro, Inês Rito Lima, Alexandre Ulisses, Tiago Mendes-Neves, Tiago Mendes-Neves, João Mendes-Moreira

2022

Abstract

The broadcast of audio-video sports content is a field with increasingly larger audiences demanding higher quality content and involvement. This growth creates the necessity to develop more content to engage the users and keep this trend. Otherwise, it may stall or even diminish. Therefore, enhancing the user experience, engagement, and involvement during live sports event broadcasts is of utmost importance. This paper proposes a solution to extract event’s information from video, resorting to Computer Vision techniques and Deep Learning algorithms. More specifically, the project encompassed the definition and implementation of field registration, object detection and tracking tasks. Focusing on football sports events, a novel dataset combining several video sources was created and used for analysis and metadata extraction. In particular, the proposed solution can detect and track players with acceptable precision using state-of-the-art methods, like YOLOv5 and DeepSORT. Furthermore, resorting to unsupervised learning techniques, the system provides team segmentation based on the colour of the players’ kits. A series of visual representations regarding the players’ movements on the field enables broadcast enrichment and increased user experience. The presented solution is framed in the H2020 DataCloud project and will be deployed in a cloud environment simplifying its access and utilisation.

Paper Citation

in Harvard Style

Couceiro M., Rito Lima I., Ulisses A., Mendes-Neves T. and Mendes-Moreira J. (2022). Tracking Data Visual Representations for Sports Broadcasting Enrichment. In - icSPORTS, ISBN , pages 0-0. DOI: 10.5220/0011551900003321

in Bibtex Style

@conference{icsports22,
author={Murilo Couceiro and Inês Rito Lima and Alexandre Ulisses and Tiago Mendes-Neves and João Mendes-Moreira},
title={Tracking Data Visual Representations for Sports Broadcasting Enrichment},
booktitle={ - icSPORTS,},
year={2022},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011551900003321},
isbn={},
}

in EndNote Style

TY - CONF

JO - - icSPORTS,
TI - Tracking Data Visual Representations for Sports Broadcasting Enrichment
SN -
AU - Couceiro M.
AU - Rito Lima I.
AU - Ulisses A.
AU - Mendes-Neves T.
AU - Mendes-Moreira J.
PY - 2022
SP - 0
EP - 0
DO - 10.5220/0011551900003321