Plane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Clouds
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 m...
| Main Author: | |
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| Format: | Thesis |
| Published: |
Curtin University
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/75305 |
| _version_ | 1848763464977219584 |
|---|---|
| author | Nguyen, Hoang Long |
| author_facet | Nguyen, Hoang Long |
| author_sort | Nguyen, Hoang Long |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T11:03:53Z |
| format | Thesis |
| id | curtin-20.500.11937-75305 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:03:53Z |
| publishDate | 2018 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-753052019-04-15T06:21:27Z Plane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Clouds Nguyen, Hoang Long 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. 2018 Thesis http://hdl.handle.net/20.500.11937/75305 Curtin University fulltext |
| spellingShingle | Nguyen, Hoang Long Plane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Clouds |
| title | Plane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Clouds |
| title_full | Plane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Clouds |
| title_fullStr | Plane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Clouds |
| title_full_unstemmed | Plane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Clouds |
| title_short | Plane Segmentation and Registration of Sparse and Heterogeneous Mobile Laser Scanning Point Clouds |
| title_sort | plane segmentation and registration of sparse and heterogeneous mobile laser scanning point clouds |
| url | http://hdl.handle.net/20.500.11937/75305 |