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dc.contributor.authorYu, Qian
dc.contributor.authorHelmholz, Petra
dc.contributor.authorBelton, David
dc.contributor.authorWest, Geoff
dc.contributor.editorJ. Jiang
dc.contributor.editorH. Zhang
dc.date.accessioned2017-01-30T15:19:05Z
dc.date.available2017-01-30T15:19:05Z
dc.date.created2014-10-26T20:00:25Z
dc.date.issued2014
dc.identifier.citationYu, Q. and Helmholz, P. and Belton, D. and West, G. 2014. Grammar-based Automatic 3D Model Reconstruction from Terrestrial Laser Scanning Data, in J. Jiang and H. Zhang (ed), ISPRS Technical Commission IV Symposium, May 14-16 2014, pp. 335-340. Suzhou, China: International Society for Photogrammetry and Remote Sensing.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/45168
dc.description.abstract

The automatic reconstruction of 3D buildings has been an important research topic during the last years. In this paper, a novel method is proposed to automatically reconstruct the 3D building models from segmented data based on pre-defined formal grammar and rules. Such segmented data can be extracted e.g. from terrestrial or mobile laser scanning devices. Two steps are considered in detail. The first step is to transform the segmented data into 3D shapes, for instance using the DXF (Drawing Exchange Format) format which is a CAD data file format used for data interchange between AutoCAD and other program. Second, we develop a formal grammar to describe the building model structure and integrate the pre-defined grammars into the reconstruction process. Depending on the different segmented data, the selected grammar and rules are applied to drive the reconstruction process in an automatic manner. Compared with other existing approaches, our proposed method allows the model reconstruction directly from 3D shapes and takes the whole building into account.

dc.publisherInernational Society for Photogrammetry and Remote Sensing
dc.subjectbuilding
dc.subjectModel
dc.subject3D
dc.subjectreconstruction
dc.subjectgrammar
dc.titleGrammar-based Automatic 3D Model Reconstruction from Terrestrial Laser Scanning Data
dc.typeConference Paper
dcterms.source.startPage335
dcterms.source.endPage340
dcterms.source.titleThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-4
dcterms.source.seriesThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-4
dcterms.source.conferenceISPRS Technical Commission IV Symposium
dcterms.source.conference-start-dateMay 14 2014
dcterms.source.conferencelocationSuzhou, China
dcterms.source.placeCanada
curtin.note

This article is published under the Open Access publishing model and distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/ Please refer to the licence to obtain terms for any further reuse or distribution of this work.

curtin.departmentDepartment of Spatial Sciences
curtin.accessStatusOpen access


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