Direct 3D Body Measurement Estimation from Sparse Landmarks

David Bojanić, Kristijan Bartol, Tomislav Petković, Tomislav Pribanić

2024

Abstract

The current state-of-the-art 3D anthropometry extraction methods are either template-based or landmark-based. Template-based methods fit a statistical human body model to a 3D scan and extract complex features from the template to learn the body measurements. The fitting process is usually an optimization process, sensitive to its hyperparameters. Landmark-based methods use body proportion heuristics to estimate the landmark locations on the body in order to derive the measurements. Length measurements are derived as distances between landmarks, whereas circumference measurements are derived as cross-sections of the body and a plane defined at the desired landmark location. This makes it very susceptible to noise in the 3D scan data. To address these issues, we propose a simple learning method that infers the body measurements directly using the landmarks defined on the body. Our method avoids fitting a body model, extracting complex features, using heuristics, and handling noise in the data. We compare our method on the CAESAR dataset and show that using a simple method coupled with sparse landmark data can compete with state-of-the-art methods. To take a step towards open-source 3D anthropometry, we make our code available at https:/github.com/DavidBoja/Landmarks2Anthropometry.

Paper Citation

in Harvard Style

Bojanić D., Bartol K., Petković T. and Pribanić T. (2024). Direct 3D Body Measurement Estimation from Sparse Landmarks. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 524-531. DOI: 10.5220/0012384000003660

in Bibtex Style

@conference{visapp24,
author={David Bojanić and Kristijan Bartol and Tomislav Petković and Tomislav Pribanić},
title={Direct 3D Body Measurement Estimation from Sparse Landmarks},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP},
year={2024},
pages={524-531},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012384000003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP
TI - Direct 3D Body Measurement Estimation from Sparse Landmarks
SN - 978-989-758-679-8
AU - Bojanić D.
AU - Bartol K.
AU - Petković T.
AU - Pribanić T.
PY - 2024
SP - 524
EP - 531
DO - 10.5220/0012384000003660
PB - SciTePress