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dc.contributor.authorSiti Nurhashima, Mohd Isa
dc.contributor.authorShazmin Aniza, Abdul Shukor
dc.contributor.authorI., Maarof
dc.contributor.authorZainor Ridzuan, Yahya
dc.contributor.authorNorasmadi, Abdul Rahim
dc.contributor.authorAmmar, Zakaria
dc.contributor.authorA. H., Abdullah
dc.contributor.authorR., Wong
dc.date.accessioned2020-10-20T00:32:33Z
dc.date.available2020-10-20T00:32:33Z
dc.date.issued2019
dc.identifier.citationThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4-W16, 2019, pages 425-432en_US
dc.identifier.issn1682-1750 (Print)
dc.identifier.issn2194-9034 (Online)
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/68469
dc.descriptionLink to publisher's homepage at https://www.isprs.org/publications/archives.aspxen_US
dc.description.abstractIn this paper, pairwise coarse registration is presented using real world point cloud data obtained by terrestrial laser scanner and without information on reference marker on the scene. The challenge in the data is because of multi-scanning which caused large data size in millions of points due to limited range about the scene generated from side view. Furthermore, the data have a low percentage of overlapping between two scans, and the point cloud data were acquired from structures with geometrical symmetry which leads to minimal transformation during registration process. To process the data, 3D Harris keypoint is used and coarse registration is done by Iterative Closest Point (ICP). Different sampling methods were applied in order to evaluate processing time for further analysis on different voxel grid size. Then, Root Means Squared Error (RMSE) is used to determine the accuracy of the approach and to study its relation to relative orientation of scan by pairwise registration. The results show that the grid average downsampling method gives shorter processing time with reasonable RMSE in finding the exact scan pair. It can also be seen that grid step size is having an inverse relationship with downsampling points. This setting is used to test on smaller overlapping data set of other heritage building. Evaluation on relative orientation is studied from transformation parameter for both data set, where Data set I, which higher overlapping data gives better accuracy which may be due to the small distance between the two point clouds compared to Data set II.en_US
dc.language.isoenen_US
dc.publisherCopernicus Publicationsen_US
dc.subjectPoint clouden_US
dc.subjectTerrestrial Laser Scanneren_US
dc.subjectPairwise Registrationen_US
dc.subject3D Keypointsen_US
dc.subjectHeritage buildingen_US
dc.subjectKeypoint extractionen_US
dc.titleOrientation-based pairwise coarse registration with markerless terrestrial laser scansen_US
dc.typeArticleen_US
dc.identifier.urlhttps://www.isprs.org/publications/archives.aspx
dc.identifier.doihttps://doi.org/10.5194/isprs-archives-XLII-4-W16-425-2019
dc.contributor.urlsitinurhashima.isa@gmail.comen_US
dc.contributor.urlshazmin@unimap.edu.myen_US


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