Tracking Data Visual Representations for Sports Broadcasting Enrichment

• Type: Article in International Conference Proceedings Book
• Date: 2022

Authors

Couceiro, M (Author) Other; Lima, IR (Author) Other; Ulisses, A (Author) Other; Neves, TM (Author) Other; João Mendes-Moreira (Author) FEUP

Conference proceedings International

Title: icSPORTS2022 - Proceedings of the 10th International Conference on Sport Sciences Research and Technology Support

Pages: 125-131

10th International Conference on Sport Sciences Research and Technology Support

Valletta, Malta, 27-28 de Outubro de 2022

Indexing

Scopus - 0 Citations

Other information

Authenticus ID: P-00X-RY7

Abstract (EN): 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. Copyright © 2022 by SCITEPRESS ¿ Science and Technology Publications, Lda. All rights reserved.

Language: English

Type (Professor's evaluation): Scientific