Generalized Torsion-Curvature Scale Space Descriptor for 3-Dimensional Curves

Lynda Ayachi, Majdi Jribi, Faouzi Ghorbel

2023

Abstract

In this paper, we propose a new method for representing 3D curves called the Generalized Torsion Curvature Scale Space (GTCSS) descriptor. This method is based on the calculation of curvature and torsion measures at different scales, and it is invariant under rigid transformations. To address the challenges associated with estimating these measures, we employ a multi-scale technique in our approach. We evaluate the effectiveness of our method through experiments, where we extract space curves from 3D objects and apply our method to pose estimation tasks. Our results demonstrate the effectiveness of the GTCSS descriptor for representing 3D curves and its potential for use in a variety of computer vision applications.

Paper Citation

in Harvard Style

Ayachi L., Jribi M. and Ghorbel F. (2023). Generalized Torsion-Curvature Scale Space Descriptor for 3-Dimensional Curves. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-626-2, pages 185-190. DOI: 10.5220/0011895500003411

in Bibtex Style

@conference{icpram23,
author={Lynda Ayachi and Majdi Jribi and Faouzi Ghorbel},
title={Generalized Torsion-Curvature Scale Space Descriptor for 3-Dimensional Curves},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2023},
pages={185-190},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011895500003411},
isbn={978-989-758-626-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Generalized Torsion-Curvature Scale Space Descriptor for 3-Dimensional Curves
SN - 978-989-758-626-2
AU - Ayachi L.
AU - Jribi M.
AU - Ghorbel F.
PY - 2023
SP - 185
EP - 190
DO - 10.5220/0011895500003411