A Framework for Position Uncertainty of Unorganised Three-Dimensional Point Clouds from Near-Monostatic Laser Scanners Using Covariance Analysis
Position uncertainty is one of the most important quantities of an unorganised three- dimensional point clouds since it provides the confidence level of any parametric estimation such as surface normal vector estimation and the registration of point clouds. We present an explicit form of position un...
| Main Authors: | , , |
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| Format: | Conference Paper |
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International Society for Photogrammetry and Remote Sensing
2005
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| Online Access: | http://hdl.handle.net/20.500.11937/45224 |
| _version_ | 1848757223659929600 |
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| author | Bae, Kwang-ho Belton, David Lichti, Derek |
| author2 | G. Vosselman |
| author_facet | G. Vosselman Bae, Kwang-ho Belton, David Lichti, Derek |
| author_sort | Bae, Kwang-ho |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Position uncertainty is one of the most important quantities of an unorganised three- dimensional point clouds since it provides the confidence level of any parametric estimation such as surface normal vector estimation and the registration of point clouds. We present an explicit form of position uncertainty based on the covariance analysis of a point. In addition, an explicit form of the variance of an estimated surface normal vector and an algorithm to evaluate an optimal size of the neighbourhood of a point which minimises the variance of the estimated normal vector are presented. |
| first_indexed | 2025-11-14T09:24:41Z |
| format | Conference Paper |
| id | curtin-20.500.11937-45224 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:24:41Z |
| publishDate | 2005 |
| publisher | International Society for Photogrammetry and Remote Sensing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-452242022-10-20T06:33:07Z A Framework for Position Uncertainty of Unorganised Three-Dimensional Point Clouds from Near-Monostatic Laser Scanners Using Covariance Analysis Bae, Kwang-ho Belton, David Lichti, Derek G. Vosselman C Brenner point cloud three-dimensional position uncertainty laser scanning Position uncertainty is one of the most important quantities of an unorganised three- dimensional point clouds since it provides the confidence level of any parametric estimation such as surface normal vector estimation and the registration of point clouds. We present an explicit form of position uncertainty based on the covariance analysis of a point. In addition, an explicit form of the variance of an estimated surface normal vector and an algorithm to evaluate an optimal size of the neighbourhood of a point which minimises the variance of the estimated normal vector are presented. 2005 Conference Paper http://hdl.handle.net/20.500.11937/45224 International Society for Photogrammetry and Remote Sensing restricted |
| spellingShingle | point cloud three-dimensional position uncertainty laser scanning Bae, Kwang-ho Belton, David Lichti, Derek A Framework for Position Uncertainty of Unorganised Three-Dimensional Point Clouds from Near-Monostatic Laser Scanners Using Covariance Analysis |
| title | A Framework for Position Uncertainty of Unorganised Three-Dimensional Point Clouds from Near-Monostatic Laser Scanners Using Covariance Analysis |
| title_full | A Framework for Position Uncertainty of Unorganised Three-Dimensional Point Clouds from Near-Monostatic Laser Scanners Using Covariance Analysis |
| title_fullStr | A Framework for Position Uncertainty of Unorganised Three-Dimensional Point Clouds from Near-Monostatic Laser Scanners Using Covariance Analysis |
| title_full_unstemmed | A Framework for Position Uncertainty of Unorganised Three-Dimensional Point Clouds from Near-Monostatic Laser Scanners Using Covariance Analysis |
| title_short | A Framework for Position Uncertainty of Unorganised Three-Dimensional Point Clouds from Near-Monostatic Laser Scanners Using Covariance Analysis |
| title_sort | framework for position uncertainty of unorganised three-dimensional point clouds from near-monostatic laser scanners using covariance analysis |
| topic | point cloud three-dimensional position uncertainty laser scanning |
| url | http://hdl.handle.net/20.500.11937/45224 |