EVALUATING VOXEL ENABLED SCALABLE INTERSECTION OF LARGE POINT CLOUDS
Laser scanning has become a well established surveying solution for obtaining 3D geo-spatial information on objects and environment. Nowadays scanners acquire up to millions of points per second which makes point cloud huge. Laser scanning is widely applied from airborne, carborne and stable platfor...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2015-08-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-3-W5/25/2015/isprsannals-II-3-W5-25-2015.pdf |
| Summary: | Laser scanning has become a well established surveying solution for obtaining 3D geo-spatial information on objects and environment.
Nowadays scanners acquire up to millions of points per second which makes point cloud huge. Laser scanning is widely applied from
airborne, carborne and stable platforms, resulting in point clouds obtained at different attitudes and with different extents. Working with
such different large point clouds makes the determination of their overlapping area necessary but often time consuming. In this paper,
a scalable point cloud intersection determination method is presented based on voxels. The method takes two overlapping point clouds
as input. It consecutively resamples the input point clouds according to a preset voxel cell size. For all non-empty cells the center of
gravity of the points in contains is computed. Consecutively for those centers it is checked if they are in a voxel cell of the other point
cloud. The same process is repeated after interchanging the role of the two point clouds. The quality of the results is evaluated by the
distance to the pints from the other data set. Also computation time and quality of the results are compared for different voxel cell
sizes. The results are demonstrated on determining he intersection between an airborne and carborne laser point clouds and show that
the proposed method takes 0.10%, 0.15%, 1.26% and 14.35% of computation time compared the the classic method when using cell
sizes of of 10, 8, 5 and 3 meters respectively. |
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| ISSN: | 2194-9042 2194-9050 |