COMPUTING ARBITRARILY LARGE MESHES WITH LEVEL-OF-DETAIL SUPPORT FOR CESIUM 3D TILES

Autor(en): Hillmann, Malte
Igelbrink, Malte
Wiemann, Thomas 
Herausgeber: Nuchter, A.
Grussenmeyer, P.
Kersten, T.
Stichwörter: 3D Surface Reconstruction; Cesium; High resolution; Image reconstruction; Large-scales; Laser scanned; Level-of-detail; Level-of-Detail Rendering; Mesh Simplification; Mesh simplifications; Octrees; Point-clouds; Rendering (computer graphics); Three dimensional computer graphics; Web-based Visualization; Websites
Erscheinungsdatum: 2022
Herausgeber: International Society for Photogrammetry and Remote Sensing
Journal: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volumen: 48
Ausgabe: 2/W1-2022
Startseite: 109 – 116
Zusammenfassung: 
In this paper we present an approach to compute arbitrarily sized meshes of large scale environments. The meshes can be reconstructed from laser-scanned point clouds or existing high-resolution meshes. The algorithm automatically builds a level of detail hierarchy in the Cesium 3D Tiles format using an octree partition. The main contribution of this paper is a method that ensures that the generated meshes for each level-of-detail stage are computed in a consistent manner to minimize visual artifacts between different detail levels during rendering. Furthermore, both the reconstruction and simplification algorithm are designed to constrain the memory consumption, which enables to process even very large data sets on consumer-grade hardware. The export into the Cesium 3D Tiles format allows to render such large meshes efficiently in all web-based viewers that support this format. In our experiments we evaluate the method on different datasets and assess the visual quality during the rendering process and analyze the memory footprint as well as the runtime behaviour. © Author(s) 2022. CC BY 4.0 License.
Beschreibung: 
Cited by: 0; Conference name: 7th International Workshop on LowCost 3D - Sensors, Algorithms, Applications; Conference date: 15 December 2022 through 16 December 2022; Conference code: 185012; All Open Access, Gold Open Access
ISSN: 1682-1750
DOI: 10.5194/isprs-archives-XLVIII-2-W1-2022-109-2022
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144312105&doi=10.5194%2fisprs-archives-XLVIII-2-W1-2022-109-2022&partnerID=40&md5=4db3680708b17af88af81b33a1b70790

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