Supporting multi-resolution out-of-core rendering of massive LiDAR point clouds through non-redundant data structures
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Supporting multi-resolution out-of-core rendering of massive LiDAR point clouds through non-redundant data structuresFecha
2019-03Cita bibliográfica
David Deibe, Margarita Amor & Ramón Doallo (2019) Supporting multi-resolution out-of-core rendering of massive LiDAR point clouds through non-redundant data structures, International Journal of Geographical Information Science, 33:3, 593-617, DOI: 10.1080/13658816.2018.1549734
Resumen
[Abstract]: In recent years, the evolution and improvement of LiDAR (Light Detection and Ranging) hardware has increased the quality and quantity of the gathered data, making the storage, processing and management thereof particularly challenging. In this work we present a novel, multi-resolution, out-of-core technique, used for web-based visualization and implemented through a non-redundant, data point organization method, which we call Hierarchically Layered Tiles (HLT), and a tree-like structure called Tile Grid Partitioning Tree (TGPT). The design of these elements is mainly focused on attaining very low levels of memory consumption, disk storage usage and network traffic on both, client and server-side, while delivering high-performance interactive visualization of massive LiDAR point clouds (up to 28 billion points) on multiplatform environments (mobile devices or desktop computers). HLT and TGPT were incorporated and tested in ViLMA (Visualization for LiDAR data using a Multi-resolution Approach), our own web-based visualization software specially designed to work with massive LiDAR point clouds.
Palabras clave
LiDAR
Web-visualization
Efficient data structures
Multi-resolution
Out-of-core
Web-visualization
Efficient data structures
Multi-resolution
Out-of-core
Descripción
This is an Accepted Manuscript of an article published by Taylor & Francis in INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE on 28 Nov 2018, available at: https://doi.org/10.1080/13658816.2018.1549734
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Atribución-NoComercial-SinDerivadas 3.0 España
ISSN
1365-8824