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A fast and effective way to improve the merging accuracy of multi-view point cloud data

Li, Feng, Longstaff, Andrew P., Fletcher, Simon and Myers, Alan (2011) A fast and effective way to improve the merging accuracy of multi-view point cloud data. In: Proceedings of the 17th International Conference on Automation & Computing. Chinese Automation and Computing Society, Huddersfield, UK, pp. 18-21. ISBN 978-1-86218-098-7

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Abstract

In reverse engineering, in order to meet the requirements for model reconstruction, it is often necessary to locate and merge the different-view-measured cloud data in a global coordinate system. Many merging methods have been proposed, the method of three datum points is one of them and the registration precision of model data depends on the precision of three datum points which are selected. This paper introduces a new development of the “centroid of apexes” method instead of the former datum points to improve the three points positioning algorithm, the effectiveness of the methods is validated with experimental results and a revised algorithm is presented.

Item Type: Book Chapter
Subjects: T Technology > T Technology (General)
T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
School of Computing and Engineering > Automotive Engineering Research Group
School of Computing and Engineering > Centre for Precision Technologies > Engineering Control and Machine Performance Research Group
School of Computing and Engineering > High-Performance Intelligent Computing
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge

School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
Related URLs:
Depositing User: Feng Li
Date Deposited: 22 Sep 2011 14:10
Last Modified: 22 Sep 2011 14:10
URI: http://eprints.hud.ac.uk/id/eprint/11500

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