A Hierarchical Classification for Automatic Assessment of the Reception Quality Using Videos of Volleyball and Deep Learning

Shota Nako, Hiroyuki Ogata, Taiji Matsui, Itsuki Hamada, Jun Ohya

2025

Abstract

To automate the assessment of the reception quality in volleyball games, this paper proposes a hierarchical classification method that uses deep learning methods that are trained using single view videos acquired in actual matches and the data recorded manually using Data Volley. The hierarchical classification consists of the three steps: the first step for judging whether the player is in front of (Front) or behind (Back) the net in the court, the second step for discriminating the best quality pass (A-pass) and second best pass (B-pass) vs. the third best pass (C-pass), and the third step for discriminating A-pass vs B-pass. Experiments that compare six class classification with the proposed hierarchical classification were conducted, where the former classifies the six classes: Front A-pass, Front B-pass, Front C-pass and Back A-pass, Back B-pass, Back C-pass. Two TimeSformer models were used as video classification models: TimeSformer-L and TimeSformer-HR. Also, two data sets of different lengths were used. Dataset1 is longer than Dataset2. Different sampling rates were set for each combination of dataset and model. Experimental results demonstrate that the proposed hierarchical classification outperforms the six class classification, clarifying the best combinations of TimeSformer model, Dataset and sampling rate.

Paper Citation

in Harvard Style

Nako S., Ogata H., Matsui T., Hamada I. and Ohya J. (2025). A Hierarchical Classification for Automatic Assessment of the Reception Quality Using Videos of Volleyball and Deep Learning. In Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-730-6, SciTePress, pages 673-680. DOI: 10.5220/0013238000003905

in Bibtex Style

@conference{icpram25,
author={Shota Nako and Hiroyuki Ogata and Taiji Matsui and Itsuki Hamada and Jun Ohya},
title={A Hierarchical Classification for Automatic Assessment of the Reception Quality Using Videos of Volleyball and Deep Learning},
booktitle={Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2025},
pages={673-680},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013238000003905},
isbn={978-989-758-730-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - A Hierarchical Classification for Automatic Assessment of the Reception Quality Using Videos of Volleyball and Deep Learning
SN - 978-989-758-730-6
AU - Nako S.
AU - Ogata H.
AU - Matsui T.
AU - Hamada I.
AU - Ohya J.
PY - 2025
SP - 673
EP - 680
DO - 10.5220/0013238000003905
PB - SciTePress