• search hit 1 of 6
Back to Result List

Interactive and View-Dependent See-Through Lenses for Massive 3D Point Clouds

  • 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 of3D 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.show moreshow less

Export metadata

Additional Services

Search Google Scholar Statistics
Metadaten
Author details:Sören DischerORCiDGND, Rico RichterORCiDGND, Jürgen Roland Friedrich DöllnerORCiDGND
DOI:https://doi.org/10.1007/978-3-319-25691-7_3
ISBN:978-3-319-25691-7
ISBN:978-3-319-25689-4
ISSN:1863-2246
Title of parent work (English):Advances in 3D Geoinformation
Publisher:Springer
Place of publishing:Cham
Publication type:Article
Language:English
Date of first publication:2016/10/18
Publication year:2016
Release date:2022/09/28
Tag:3D point clouds; LIDAR; Point-based rendering; Visualization
Number of pages:14
First page:49
Last Page:62
Organizational units:An-Institute / Hasso-Plattner-Institut für Digital Engineering gGmbH
DDC classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Peer review:Referiert
Accept ✔
This website uses technically necessary session cookies. By continuing to use the website, you agree to this. You can find our privacy policy here.