Selviah, DR;
(2020)
Automated 3D Point Cloud Data Processing Using AI.
Geomatics World
, 28
(1)
pp. 18-21.
Preview |
Text
Selviah_Selviah Point Cloud Processing ID edit - 2.pdf - Accepted Version Download (1MB) | Preview |
Abstract
Instruments for digitising the 3D real environment are becoming smaller, more lightweight, lower cost and more robust and so are finding widespread usage, not only on surveying tripods for the highest accuracy, but also on mobile platforms such as autonomous vehicles, drones, helicopters, aircraft, robotic vacuum cleaners, trains, mobile phones, satellites and Martian rovers. Lidar uses laser scanning while photogrammetry records images from one or more cameras which may be moving. Each laser scan records tens of millions of data point position and colour in a point cloud and hundreds of such point clouds may be combined. This article discusses the challenges such as management, storage, registration, fusion, extraction of useful and actionable information that many companies and organisations face after obtaining vast 3D point cloud datasets.
| Type: | Article |
|---|---|
| Title: | Automated 3D Point Cloud Data Processing Using AI |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://www.geomatics-world.co.uk/magazine/spring-... |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10095489 |
Archive Staff Only
 |
View Item |
