Farahat, Mostafa, Soubra, Hassan, Moulla, Donatien Koulla et Abran, Alain.
2026.
« Enhancing handball analytics with computer vision and machine learning: An exploratory experiment ».
Future Internet, vol. 18, nº 4.
Prévisualisation |
PDF
Abran-A-2026-33727.pdf - Version publiée Licence d'utilisation : Creative Commons CC BY. Télécharger (2MB) | Prévisualisation |
Résumé
Recent advancements in artificial intelligence (AI) have strengthened the interaction between sports and digital technologies. However, unlike widely studied sports such as football and basketball, handball has received limited attention from the scientific community, despite its fast-paced nature and strategic importance. This study focuses on object detection in handball and targets key entities, such as players, referees, goalkeepers, and the ball. A comprehensive dataset was created through a collaborative annotation process, consisting of annotated images extracted from real handball games. The YOLOv8 model was then trained and evaluated on this dataset to assess its effectiveness in entity recognition. The proposed approach achieved an object detection accuracy of 86.8% on a relatively small held-out test set, providing an indicative first benchmark for the application of state-of-the-art machine learning models to handball. To the best of our knowledge, the dataset generated in this study is the first comprehensive collection of annotated handball images, providing a valuable resource for further research. By bridging sports analytics and computer vision, this study contributes to the advancement of performance assessment in handball. These exploratory results suggest potential directions for future real-time systems and practical applications, such as improved understanding of player performance, team dynamics, and strategic decision-making.
| Type de document: | Article publié dans une revue, révisé par les pairs |
|---|---|
| Chercheur(-euse): | Chercheur(-euse) Abran, Alain |
| Affiliation: | Génie logiciel et des technologies de l'information |
| Date de dépôt: | 12 mai 2026 14:39 |
| Dernière modification: | 22 mai 2026 22:29 |
| URI: | https://espace2.etsmtl.ca/id/eprint/33727 |
Actions (Authentification requise)
 |
Dernière vérification avant le dépôt |