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Correspondence rejection by trilateration for 3D point cloud registration

Lachhani, K; Duan, J; Baghsiahi, H; Willman, E; Selviah, DR; (2015) Correspondence rejection by trilateration for 3D point cloud registration. In: 14th IAPR International Conference on Machine Vision Applications (MVA). (pp. pp. 337-340). IEEE: Tokyo, Japan. Green open access

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Abstract

Recent years have shown increases in virtual 3D perception and applications, many of these applications require 3D model reconstruction from high quality LIDAR scans. High quality 3D models may be acquired from a collection of overlapping LIDAR scans which need to be registered or aligned to a common coordinate system. This paper investigates the use of a novel implementation of trilateration for correspondence rejection in highly accurate 3D point cloud registration. It is shown that from a synthesized correspondence set of size 100 containing 85% outliers, all or most of the remaining 15% inliers can be retrieved. The trilateration problem is solved for all 4-combinations of correspondence elements from which the true correspondence subsets are easily identifiable. It is also shown that this method's performance may be greatly affected by noisy distance measurements, however the method works well for distance measurements typically acquired by LIDAR systems. Lastly, unnecessarily large sizes of correspondence sets can quickly make the method computationally expensive if all combination subsets require to be evaluated.

Type: Proceedings paper
Title: Correspondence rejection by trilateration for 3D point cloud registration
Event: 14th IAPR International Conference on Machine Vision Applications (MVA), 2015
ISBN-13: 9784901122153
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/MVA.2015.7153199
Publisher version: http://dx.doi.org/10.1109/MVA.2015.7153199
Additional information: Copyright © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: image denoising, image registration, optical radar, radar imaging
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1471477
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