TY  - GEN
A1  - Discher, Sören
A1  - Richter, Rico
A1  - Döllner, Jürgen Roland Friedrich
ED  - Spencer, SN
T1  - A scalable webGL-based approach for visualizing massive 3D point clouds using semantics-dependent rendering techniques
T2  - Web3D 2018: The 23rd International ACM Conference on 3D Web Technology
N2  - 3D point cloud technology facilitates the automated and highly detailed digital acquisition of real-world environments such as assets, sites, cities, and countries; the acquired 3D point clouds represent an essential category of geodata used in a variety of geoinformation applications and systems. In this paper, we present a web-based system for the interactive and collaborative exploration and inspection of arbitrary large 3D point clouds. Our approach is based on standard WebGL on the client side and is able to render 3D point clouds with billions of points. It uses spatial data structures and level-of-detail representations to manage the 3D point cloud data and to deploy out-of-core and web-based rendering concepts. By providing functionality for both, thin-client and thick-client applications, the system scales for client devices that are vastly different in computing capabilities. Different 3D point-based rendering techniques and post-processing effects are provided to enable task-specific and data-specific filtering and highlighting, e.g., based on per-point surface categories or temporal information. A set of interaction techniques allows users to collaboratively work with the data, e.g., by measuring distances and areas, by annotating, or by selecting and extracting data subsets. Additional value is provided by the system's ability to display additional, context-providing geodata alongside 3D point clouds and to integrate task-specific processing and analysis operations. We have evaluated the presented techniques and the prototype system with different data sets from aerial, mobile, and terrestrial acquisition campaigns with up to 120 billion points to show their practicality and feasibility.
KW  - 3D Point Clouds
KW  - web-based rendering
KW  - point-based rendering
Y1  - 2018
SN  - 978-1-4503-5800-2
U6  - https://doi.org/10.1145/3208806.3208816
SP  - 1
EP  - 9
PB  - Association for Computing Machinery
CY  - New York
ER  -