Evaluation of Body Parts Representations in Motion Reconstruction

Philippe de Clermont Gallerande, Philippe de Clermont Gallerande, Quentin Avril, Philippe Henri Gosselin, Ferran Argelaguet, Ludovic Hoyet

2025

Abstract

Acquiring, encoding, transmitting, decoding, and displaying motion signals is an essential challenge in our new world of interconnected immersive applications (XR, online games etc.). In addition to being potentially disturbed by multiple factors (e.g., signal noise, latency, packet loss), this motion data should be modifiable and customizable to fit the needs of specific applications. Simultaneously, several approaches have successfully proposed to explicitly integrate the semantics of the human body in a deep learning framework by separating it into smaller parts. We propose to use such an approach to obtain a robust streamed animation data. Specifically, we create and train several neural networks on the motion of different body parts independently from each other. We further compare the performances of several body decompositions using multiple objective reconstruction metrics. Eventually, we show that this Body Parts approach brings new opportunities compared to a compact one, such as a perfectly partitioned and more interpretable motion data, while obtaining comparable reconstruction results.

Paper Citation

in Harvard Style

de Clermont Gallerande P., Avril Q., Gosselin P., Argelaguet F. and Hoyet L. (2025). Evaluation of Body Parts Representations in Motion Reconstruction. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP; ISBN 978-989-758-728-3, SciTePress, pages 53-64. DOI: 10.5220/0013138200003912

in Bibtex Style

@conference{grapp25,
author={Philippe de Clermont Gallerande and Quentin Avril and Philippe Henri Gosselin and Ferran Argelaguet and Ludovic Hoyet},
title={Evaluation of Body Parts Representations in Motion Reconstruction},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP},
year={2025},
pages={53-64},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013138200003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP
TI - Evaluation of Body Parts Representations in Motion Reconstruction
SN - 978-989-758-728-3
AU - de Clermont Gallerande P.
AU - Avril Q.
AU - Gosselin P.
AU - Argelaguet F.
AU - Hoyet L.
PY - 2025
SP - 53
EP - 64
DO - 10.5220/0013138200003912
PB - SciTePress