A vision-based system to support tactical and physical analyses of futsal teams

Abstract

This paper presents a vision-based system to support the tactical and physical analyses of futsal teams. Most parts of the current analyses in this sport are manually performed, while the existing solutions based on automatic approaches are frequently composed by costly and complex tools, developed for another kind of team sports, making it difficult for their adoption by futsal teams. Our system, on the other hand, represents a simple yet efficient dedicated solution, which is based on the analyses of image sequences captured by a single stationary camera used to obtain top-view images of the entire court. We use adaptive background subtraction and blob analysis to detect players, as well as particle filters to track them in every video frame. The system determines the distance travelled by each player, his/her minimum and maximum speeds, as well as generating heat maps that describe players’ occupancy during the match. To present the collected data, our system uses a specially developed mobile application. Experimental results with image sequences of an official match and a training match show that our system provides data with global minimum tracking errors below 40 cm, demanding on 25 ms to process each frame and, thus, demonstrating its high application potential.

Authors: Pedro H. C. de Padua, Flavio L. C. P, Marconi de A Pereira, Marco TD Sousa , Matheus B. de Oliveira and Elizabeth F Wanner

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