Plane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Clouds
dc.contributor.author | Nguyen, Hoang Long | |
dc.contributor.supervisor | David Belton | en_US |
dc.date.accessioned | 2019-04-15T06:21:27Z | |
dc.date.available | 2019-04-15T06:21:27Z | |
dc.date.issued | 2018 | en_US |
dc.identifier.uri | http://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.publisher | Curtin University | en_US |
dc.title | Plane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Clouds | en_US |
dc.type | Thesis | en_US |
dcterms.educationLevel | PhD | en_US |
curtin.department | School of Earth and Planetary Sciences | en_US |
curtin.accessStatus | Open access | en_US |
curtin.faculty | Science and Engineering | en_US |