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Authors: Matija Burić 1 ; Miran Pobar 2 and Marina Ivašić-Kos 2

Affiliations: 1 Hrvatska elektroprivreda d.d., SIT Rijeka, Kumičićeva 13, Rijeka, Croatia ; 2 Department of Informatics, University of Rijeka, Rijeka, Croatia

ISBN: 978-989-758-351-3

Keyword(s): Object Detector, Convolutional Neural Networks, YOLO, Sports, Handball.

Abstract: In this paper, we consider the task of detecting the players and sports balls in real-world handball images, as a building block for action recognition. Detecting the ball is still a challenge because it is a very small object that takes only a few pixels in the image but carries a lot of information relevant to the interpretation of scenes. Balls can vary greatly regarding color and appearance due to various distances to the camera and motion blur. Occlusion is also present, especially as handball players carry the ball in their hands during the game and it is understood that the player with the ball is a key player for the current action. Handball players are located at different distances from the camera, often occluded and have a posture that differs from ordinary activities for which most object detectors are commonly learned. We compare the performance of 6 models based on the YOLOv2 object detector, trained on an image dataset of publicly available sports images and images from custom handball recordings. The performance of a person and ball detection is measured on the whole dataset and the custom part regarding mean average precision metric. (More)

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Paper citation in several formats:
Burić, M.; Pobar, M. and Ivasic-Kos, M. (2019). Adapting YOLO Network for Ball and Player Detection.In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-351-3, pages 845-851. DOI: 10.5220/0007582008450851

@conference{icpram19,
author={Matija Burić. and Miran Pobar. and Ivasic{-}Kos, M.},
title={Adapting YOLO Network for Ball and Player Detection},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2019},
pages={845-851},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007582008450851},
isbn={978-989-758-351-3},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Adapting YOLO Network for Ball and Player Detection
SN - 978-989-758-351-3
AU - Burić, M.
AU - Pobar, M.
AU - Ivasic-Kos, M.
PY - 2019
SP - 845
EP - 851
DO - 10.5220/0007582008450851

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