Color Supported Generalized-ICP

Michael Korn, Martin Holzkothen, Josef Pauli

2014

Abstract

This paper presents a method to support point cloud registration with color information. For this purpose we integrate L*a*b* color space information into the Generalized Iterative Closest Point (GICP) algorithm, a state-of-the-art Plane-To-Plane ICP variant. A six-dimensional k-d tree based nearest neighbor search is used to match corresponding points between the clouds. We demonstrate that the additional effort in general does not have an immoderate impact on the runtime, since the number of iterations can be reduced. The influence on the estimated 6 DoF transformations is quantitatively evaluated on six different datasets. It will be shown that the modified algorithm can improve the results without needing any special parameter adjustment.

Paper Citation

in Harvard Style

Korn M., Holzkothen M. and Pauli J. (2014). Color Supported Generalized-ICP . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-009-3, pages 592-599. DOI: 10.5220/0004692805920599

in Bibtex Style

@conference{visapp14,
author={Michael Korn and Martin Holzkothen and Josef Pauli},
title={Color Supported Generalized-ICP},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={592-599},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004692805920599},
isbn={978-989-758-009-3},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)
TI - Color Supported Generalized-ICP
SN - 978-989-758-009-3
AU - Korn M.
AU - Holzkothen M.
AU - Pauli J.
PY - 2014
SP - 592
EP - 599
DO - 10.5220/0004692805920599