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dc.contributor.authorBelton, David
dc.contributor.authorMoncrieff, Simon
dc.contributor.authorChapman, Jane
dc.contributor.editorM. Scaioni
dc.contributor.editorR. C. Lindenbergh
dc.contributor.editorS. Oude Elberink
dc.contributor.editorD. Schneider
dc.contributor.editorF. Pirotti
dc.identifier.citationBelton, David and Moncrieff, Simon and Chapman, Jane. 2013. Processing tree point clouds using Gaussian Mixture Models, in Scaioni, M. and Lindenbergh, R.C. and Oude Elberink, S. and Schneider, D. and Pirotti, F. (ed), International Society for Photogrammetry and Remote Sensing (ISPRS) Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences, Nov 11-13 2013, II-5/W2: pp. 43-48. Antalya, Turkey: ISPRS.

While traditionally used for surveying and photogrammetric fields, laser scanning is increasingly being used for a wider range of more general applications. In addition to the issues typically associated with processing point data, such applications raise a number of new complications, such as the complexity of the scenes scanned, along with the sheer volume of data. Consequently, automated procedures are required for processing, and analysing such data. This paper introduces a method for modelling multi-modal, geometrically complex objects in terrestrial laser scanning point data; specifically, the modelling of trees. The model method comprises a number of geometric features in conjunction with a multi-modal machine learning technique. The model can then be used for contextually dependent region growing through separating the tree into its component part at the point level. Subsequently object analysis can be performed, for example, performing volumetric analysis of a tree by removing points associated with leaves. The workflow for this process is as follows: isolate individual trees within the scanned scene, train a Gaussian mixture model (GMM), separate clusters within the mixture model according to exemplar points determined by the GMM, grow the structure of the tree, and then perform volumetric analysis on the structure.

dc.subjectLaser Scanning
dc.subjectGaussian Mixture Models
dc.subjectPrincipal Component Analysis
dc.titleProcessing tree point clouds using Gaussian Mixture Models
dc.typeConference Paper
dcterms.source.titleISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-5/W2
dcterms.source.seriesISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-5/W2
dcterms.source.conference2013 ISPRS Workshop Laser Scanning 2013
dcterms.source.conference-start-dateNov 11 2013
dcterms.source.conferencelocationAntalya, Turkey
curtin.accessStatusOpen access via publisher

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