Aerial LiDAR data augmentation for direct point-cloud visualisation

Bohak, Ciril (author), Slemenik, Matej (author), Kordež, Jaka (author), Marolt, Matija (author)

Direct point-cloud visualisation is a common approach for visualising large datasets of aerial terrain LiDAR scans. However, because of the limitations of the acquisition technique, such visualisations often lack the desired visual appeal and quality, mostly because certain types of objects are incomplete or entirely missing (e.g., missing water surfaces, missing building walls and missing parts of the terrain). To improve the quality of direct LiDAR point-cloud rendering, we present a point-cloud processing pipeline that uses data fusion to augment the data with additional points on water surfaces, building walls and terrain through the use of vector maps of water surfaces and building outlines. In the last step of the pipeline, we also add colour information, and calculate point normals for illumination of individual points to make the final visualisation more visually appealing. We evaluate our approach on several parts of the Slovenian LiDAR dataset.

• Language: English
• Keywords: LiDAR, point-clouds, point-cloud visualisation, terrain reconstruction, water surface reconstruction
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FRI - Faculty of Computer and Information Science
• Publication status: Published
• Publication version: Version of Record
• Year: 2020
• Number of pages: 17 str.
• Numbering: Vol. 20, iss. 7, art. 2089
• PID: 20.500.12556/RUL-133366
• UDC: 004
• ISSN on article: 1424-8220
• DOI: 10.3390/s20072089
• COBISS.SI-ID: 1538566595
• Publication date in RUL: 24.11.2021

Record is a part of a journal

• Title: Sensors
• Shortened title: Sensors
• Publisher: MDPI
• ISSN: 1424-8220
• COBISS.SI-ID: 10176278

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
• Licensing start date: 08.04.2020

Secondary language

• Language: Slovenian
• Keywords: LiDAR, oblaki točk, vizualizacija oblakov točk, rekonstrukcija terena, rekonstrukcija vodnih površin