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Multi object tracking in soccer video focusing on occlusion detection and resolving

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Abstract

Today, due to the growth of data and the development of receiving and storing technologies, large datasets have been created in various fields, such as soccer video datasets. Since obtaining the information manually from large datasets is very difficult, an automated system to capture important information from soccer videos is strongly needed. Automated analysis of soccer videos includes many applications such as: analyzing team tactics, confirming referees’ decisions, summarizing videos, etc.

In this paper, a forward-backward algorithm is proposed to increase the performance of player detection and tracking. The purpose of this algorithm is to identify and resolve the occlusions among the players and improve the preprocessing steps (playfield extraction and field lines elimination). We also proposed a new method for each preprocessing step to improve the performance of the tracking system. The evaluations show that our tracking algorithm has performed better than previous methods (89% locally and 78% globally).

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Data availability

In this paper, we used two static datasets for our purpose that the links are as follows:

• VS-PETS 2003: http://www.eecs.qmul.ac.uk/~andrea/spevi.html

• ISSIA (spagnolo): https://pspagnolo.jimdofree.com/download/

In addition, we used four broadcast datasets which their details are as follows:

• Liverpool vs Swansea, 28 Oct 2014 EFL Cup

• Real Madrid vs Atletico Madrid, 15 Jan 2015 Copa del Rey

• Cagliari vs Milan, 28 May 2017 Serie A

• Tottenham Hotspur vs Chelsea, 01 Jan 2015 Premier League

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Authors and Affiliations

  1. Computer and Information Technology Department, Sadjad University of Technology, Mashhad, Iran

    Mehran Rastegar Sani

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Correspondence to Mehran Rastegar Sani.

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Sani, M.R. Multi object tracking in soccer video focusing on occlusion detection and resolving. Multimed Tools Appl 82, 35913–35947 (2023). https://doi.org/10.1007/s11042-023-14798-z

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