Computer Vision in Sports: Evaluation of Classical Algorithms for Ball Tracking in Volleyball

• Leandro Natálio F. Batista IFPI
• Carlos Estevão B. Sousa IFPI
• Cleidson S. de Santana IFPI
• Carlos Eduardo S. de Maria IFPI
• Felipe G. dos Santos IFPI
• Renê Douglas N. de Morais IFPI

DOI: https://doi.org/10.5753/enucompi.2025.9607

Abstract

Visual object tracking is a promising approach for applications in sports analysis. This study evaluates the performance of classical tracking algorithms, such as CSRT, KCF, MOSSE, MIL, TLD, MedianFlow, and Boosting, in the task of tracking the trajectory of a volleyball in video footage. Both professional match recordings and controlled environment videos were used. The applied metrics include IoU, FPS, and MTE. Among the algorithms, CSRT achieved the best performance in terms of accuracy, while MOSSE and KCF yielded the least satisfactory results. The findings of this study contribute to the development of applications aimed at supporting tactical and technical analysis in sports contexts.

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