Li, F. orcid.org/0000-0002-6413-3617, Hitchens, C. and Stoddart, D. (2017) A performance evaluation method to compare the multi-view point cloud data registration based on ICP algorithm and reference marker. Journal of Modern Optics, 65 (1). pp. 30-37. ISSN 0950-0340
Abstract
Registration of range images of surfaces is a fundamental problem in three-dimensional modelling. This process is performed by finding a rotation matrix and translation vector between two sets of data points requiring registration. Many techniques have been developed to solve the registration problem. Therefore, it is important to understand the accuracy of various registration techniques when we decide which technique will be selected to perform registration task. This paper presents a new approach to test and compare registration techniques in terms of accuracy. Among various registration methods, iterative closest point-based algorithms and reference marker methods are two types of commonly applied methods which are used to accomplish this task because they are easy to implement and relatively low cost. These two methods have been selected to perform a comprehensively quantitative evaluation by using the proposed method and the registration results are verified using the calibrated NPL freeform standard.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 Informa uK limited, trading as Taylor & Francis Group. This is an author produced version of a paper subsequently published in Journal of Modern Optics. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Optical metrology; registration; point clouds; iterative closest point; reference markers |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Advanced Manufacturing Institute (Sheffield) > Nuclear Advanced Manufacturing Research Centre |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Oct 2017 13:33 |
Last Modified: | 10 Nov 2023 11:53 |
Status: | Published |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Identification Number: | 10.1080/09500340.2017.1375566 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:121842 |