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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.zeige mehrzeige weniger

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Metadaten
Verfasserangaben: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
Titel des übergeordneten Werks (Englisch):Advances in 3D Geoinformation
Verlag:Springer
Verlagsort:Cham
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:18.10.2016
Erscheinungsjahr:2016
Datum der Freischaltung:28.09.2022
Freies Schlagwort / Tag:3D point clouds; LIDAR; Point-based rendering; Visualization
Seitenanzahl:14
Erste Seite:49
Letzte Seite:62
Organisationseinheiten:An-Institute / Hasso-Plattner-Institut für Digital Engineering gGmbH
DDC-Klassifikation:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Peer Review:Referiert
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