TY  - JOUR
A1  - Discher, Sören
A1  - Richter, Rico
A1  - Döllner, Jürgen Roland Friedrich
T1  - Concepts and techniques for web-based visualization and processing of massive 3D point clouds with semantics
JF  - Graphical Models
N2  - 3D point cloud technology facilitates the automated and highly detailed acquisition of real-world environments such as assets, sites, and countries. We present a web-based system for the interactive exploration and inspection of arbitrary large 3D point clouds. Our approach is able to render 3D point clouds with billions of points using spatial data structures and level-of-detail representations. Point-based rendering techniques and post-processing effects are provided to enable task-specific and data-specific filtering, e.g., based on semantics. A set of interaction techniques allows users to collaboratively work with the data (e.g., measuring distances and annotating). Additional value is provided by the system’s ability to display additional, context-providing geodata alongside 3D point clouds and to integrate processing and analysis operations. We have evaluated the presented techniques and in case studies and with different data sets from aerial, mobile, and terrestrial acquisition with up to 120 billion points to show their practicality and feasibility.
KW  - 3D Point clouds
KW  - Web-based rendering
KW  - Point-based rendering
KW  - Processing strategies
Y1  - 2019
U6  - https://doi.org/10.1016/j.gmod.2019.101036
SN  - 1524-0703
SN  - 1524-0711
VL  - 104
PB  - Elsevier
CY  - San Diego
ER  - 
TY  - JOUR
A1  - Discher, Sören
A1  - Richter, Rico
A1  - Döllner, Jürgen Roland Friedrich
T1  - Interactive and View-Dependent See-Through Lenses for Massive 3D Point Clouds
JF  - Advances in 3D Geoinformation
N2  - 3D point clouds are a digital representation of our world and used in a variety of applications. They are captured with LiDAR or derived by image-matching approaches to get surface information of objects, e.g., indoor scenes, buildings, infrastructures, cities, and landscapes. We present novel interaction and visualization techniques for heterogeneous, time variant, and semantically rich 3D point clouds. Interactive and view-dependent see-through lenses are introduced as exploration tools to enhance recognition of objects, semantics, and temporal changes within 3D point cloud depictions. We also develop filtering and highlighting techniques that are used to dissolve occlusion to give context-specific insights. All techniques can be combined with an out-of-core real-time rendering system for massive 3D point clouds. We have evaluated the presented approach with 3D point clouds from different application domains. The results show the usability and how different visualization and exploration tasks can be improved for a variety of domain-specific applications.
KW  - 3D point clouds
KW  - LIDAR
KW  - Visualization
KW  - Point-based rendering
Y1  - 2016
SN  - 978-3-319-25691-7
SN  - 978-3-319-25689-4
U6  - https://doi.org/10.1007/978-3-319-25691-7_3
SN  - 1863-2246
SP  - 49
EP  - 62
PB  - Springer
CY  - Cham
ER  -