Automatic Registration of 3D Point Cloud Sequences

Natálie Vítová, Jakub Frank, Libor Váša

2024

Abstract

Surface registration is a well-studied problem in computer graphics and triangle mesh processing. A plethora of approaches exists that align a partial 3D view of a surface to another, which is a central task in 3D scanning, where usually each scan only provides partial information about the shape of the scanned object due to occlusion. In this paper, we address a slightly different problem: a pair of depth cameras is observing a dynamic scene, each providing a sequence of partial scans. The scanning devices are assumed to remain in a constant relative position throughout the process, and therefore there exists a single rigid transformation that aligns the two sequences of partial meshes. Our objective is to find this transformation based on the data alone, i.e. without using any specialized calibration tools. This problem can be approached as a set of static mesh registration problems; however, such an interpretation leads to problems when enforcing a single global solution. We show that an appropriate modification of a previously proposed consensus-based registration algorithm is a more viable solution that exploits information from all the frames simultaneously and naturally leads to a single global solution.

Paper Citation

in Harvard Style

Vítová N., Frank J. and Váša L. (2024). Automatic Registration of 3D Point Cloud Sequences. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP; ISBN 978-989-758-679-8, SciTePress, pages 261-268. DOI: 10.5220/0012388400003660

in Bibtex Style

@conference{grapp24,
author={Natálie Vítová and Jakub Frank and Libor Váša},
title={Automatic Registration of 3D Point Cloud Sequences},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP},
year={2024},
pages={261-268},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012388400003660},
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 1: GRAPP
TI - Automatic Registration of 3D Point Cloud Sequences
SN - 978-989-758-679-8
AU - Vítová N.
AU - Frank J.
AU - Váša L.
PY - 2024
SP - 261
EP - 268
DO - 10.5220/0012388400003660
PB - SciTePress