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dc.contributor.authorNguyen, Hoang Long
dc.contributor.supervisorDavid Beltonen_US
dc.date.accessioned2019-04-15T06:21:27Z
dc.date.available2019-04-15T06:21:27Z
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11937/75305
dc.description.abstract

This research discussed and analysed the limitations of different state of the art methods for point cloud processing tasks due to the sparseness and the heterogeneousness of the MLS point clouds. A novel plane detection and segmentation method for sparse MLS point clouds is proposed. Finally, the most suitable techniques for automatic registration of MLS sparse point clouds were determined based on a new error metric for evaluation.

en_US
dc.publisherCurtin Universityen_US
dc.titlePlane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Cloudsen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentSchool of Earth and Planetary Sciencesen_US
curtin.accessStatusOpen accessen_US
curtin.facultyScience and Engineeringen_US


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