Tracking Handball Players with the DeepSORT Algorithm

Kristina Host, Marina Ivašić-Kos, Miran Pobar

2020

Abstract

In team sports scenes, such as in handball, it is common to have many players on the field performing different actions according to the rules of the game. During practice, each player has their own ball, and sequentially repeats a particular technique in order to adopt it and use it. In this paper, the focus is to detect and track all players on the handball court, so that the performance of a particular athlete, and the adoption of a particular technique can be analyzed. This is a very demanding task of multiple object tracking because players move fast, often change direction, and are often occluded or out of the camera field view. We propose a DeepSort algorithm for player tracking after the players have been detected with YOLOv3 object detector. The effectiveness of the proposed methods is evaluated on a custom set of handball scenes using standard multiple object tracking metrics. Also, common detection problems that have been observed are discussed.

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Paper Citation


in Harvard Style

Host K., Ivašić-Kos M. and Pobar M. (2020). Tracking Handball Players with the DeepSORT Algorithm. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-397-1, pages 593-599. DOI: 10.5220/0009177605930599


in Bibtex Style

@conference{icpram20,
author={Kristina Host and Marina Ivašić-Kos and Miran Pobar},
title={Tracking Handball Players with the DeepSORT Algorithm},
booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2020},
pages={593-599},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009177605930599},
isbn={978-989-758-397-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Tracking Handball Players with the DeepSORT Algorithm
SN - 978-989-758-397-1
AU - Host K.
AU - Ivašić-Kos M.
AU - Pobar M.
PY - 2020
SP - 593
EP - 599
DO - 10.5220/0009177605930599