Hasso-Plattner-Institut
  
Hasso-Plattner-Institut
Prof. Dr. Jürgen Döllner
  
 
Rico Richter

Contact

Tel.: +49-(0)331 5509-3910
Fax: +49-(0)331 5509-172
Room: H-2.26
E-Mail: rico.richter(at)hpi.de

Publikationen

Concepts and techniques for integration, analysis and visualization of massive 3D point clouds

Richter, Rico and Döllner, Jürgen
Computers, Environment and Urban Systems, vol. 45:114-124 2013

DOI: DOI: 10.1016/j.compenvurbsys.2013.07.004

Abstract:

Remote sensing methods, such as LiDAR and image-based photogrammetry, are established approaches for capturing the physical world. Professional and low-cost scanning devices are capable of generating dense 3D point clouds. Typically, these 3D point clouds are preprocessed by GIS and are then used as input data in a variety of applications such as urban planning, environmental monitoring, disaster management, and simulation. The availability of area-wide 3D point clouds will drastically increase in the future due to the availability of novel capturing methods (e.g., driver assistance systems) and low-cost scanning devices. Applications, systems, and workflows will therefore face large collections of redundant, up-to-date 3D point clouds and have to cope with massive amounts of data. Hence, approaches are required that will efficiently integrate, update, manage, analyze, and visualize 3D point clouds. In this paper, we define requirements for a system infrastructure that enables the integration of 3D point clouds from heterogeneous capturing devices and different timestamps. Change detection and update strategies for 3D point clouds are presented that reduce storage requirements and offer new insights for analysis purposes. We also present an approach that attributes 3D point clouds with semantic information (e.g., object class category information), which enables more effective data processing, analysis, and visualization. Out-of-core real-time rendering techniques then allow for an interactive exploration of the entire 3D point cloud and the corresponding analysis results. Web-based visualization services are utilized to make 3D point clouds available to a large community. The proposed concepts and techniques are designed to establish 3D point clouds as base datasets, as well as rendering primitives for analysis and visualization tasks, which allow operations to be performed directly on the point data. Finally, we evaluate the presented system, report on its applications, and discuss further research challenges.

BibTeX file

@article{RD13,
author = { Richter, Rico and Döllner, Jürgen },
title = { Concepts and techniques for integration, analysis and visualization of massive 3D point clouds },
journal = { Computers, Environment and Urban Systems },
year = { 2013 },
volume = { 45 },
pages = { 114-124 },
month = { 0 },
abstract = { Remote sensing methods, such as LiDAR and image-based photogrammetry, are established approaches for capturing the physical world. Professional and low-cost scanning devices are capable of generating dense 3D point clouds. Typically, these 3D point clouds are preprocessed by GIS and are then used as input data in a variety of applications such as urban planning, environmental monitoring, disaster management, and simulation. The availability of area-wide 3D point clouds will drastically increase in the future due to the availability of novel capturing methods (e.g., driver assistance systems) and low-cost scanning devices. Applications, systems, and workflows will therefore face large collections of redundant, up-to-date 3D point clouds and have to cope with massive amounts of data. Hence, approaches are required that will efficiently integrate, update, manage, analyze, and visualize 3D point clouds. In this paper, we define requirements for a system infrastructure that enables the integration of 3D point clouds from heterogeneous capturing devices and different timestamps. Change detection and update strategies for 3D point clouds are presented that reduce storage requirements and offer new insights for analysis purposes. We also present an approach that attributes 3D point clouds with semantic information (e.g., object class category information), which enables more effective data processing, analysis, and visualization. Out-of-core real-time rendering techniques then allow for an interactive exploration of the entire 3D point cloud and the corresponding analysis results. Web-based visualization services are utilized to make 3D point clouds available to a large community. The proposed concepts and techniques are designed to establish 3D point clouds as base datasets, as well as rendering primitives for analysis and visualization tasks, which allow operations to be performed directly on the point data. Finally, we evaluate the presented system, report on its applications, and discuss further research challenges. },
priority = { 0 }
}

Copyright Notice

last change: Mon, 24 Mar 2014 15:42:11 +0100

Vorträge

  • "Detection and Classification of Changes in Urban Areas Based on Semantic Analysis of Airborne Point Clouds", European LiDAR Mapping Forum 2014, Amsterdam, The Netherlands (12/2014) 
  • "Out-of-Core Visualization of Classified 3D Point Clouds", 3D GeoInfo 2014, Dubai, VAE (11/2014) 
  • "Effiziente Bestandsaktualisierung von 3D-Stadtmodellen durch Analyse multi temporaler 3D-Punktwolken", Workshop 3D-Stadtmodelle 2014, Bonn, Deutschland (11/2014) 
  • "Semantische Klassifizierung von 3D-Punktwolken für Stadtgebiete", Terrestrisches Laserscanning 2013, Fulda, Deutschland (12/2013) 
  • "Potentiale von massiven 3D-Punktwolkendatenströmen", Geoinformatik 2012, Braunschweig, Deutschland (03/2012) 
  • "Ein Ansatz für die Differenzanalyse zwischen 3D-Punktwolken und 3D-Referenzgeometrie", DGPF - Jahrestagung 2011, Mainz, Deutschland (04/2011)
  • "Software-Technologie für massive 3D-Punktwolken", Laserscanning –eine Methode zur Bereitstellung von Geodaten für vielfältigste Anwendungen am GFZ Potsdam, Deutschland (04/2011)
  • "Bestandsaktualisierung von 3D-Stadtmodellen durch Analyse von 3D-Punktwolken", auf der 3-Ländertagung 2010, Wien , Deutschland (07/2010)
  • "Out-of-Core Real-Time Visualization of Massive 3D Point Clouds", auf der 7th International Conference on Virtual Reality, Computer Graphics, Visualisation and Interaction in Africa, Franschoek, South Africa (06/2010)

Lehrtätigkeiten

Wintersemester 2014/2015

  •  Seminar Geovisualisierung
  •  Bachelorprojekt "3D-Punktwolken: Big Spatial Data"

Sommersemester 2014

  •  Seminar Information Visualization
  •  Bachelorprojekt "Analyse & Visualisierung von 3D-Punktwolken"

Wintersemester 2013/2014

  •  Seminar Geovisualisierung
  •  Bachelorprojekt "Analyse & Visualisierung von 3D-Punktwolken"

Sommersemester 2013

  •  Seminar Geovisualisierungsverfahren

Wintersemester 2012/2013

  •  Seminar Konzepte und Techniken der 3D-Visualisierung

Sommersemester 2012

  •  Seminar Geovisualisierungsverfahren

Wintersemester 2011/2012

  •  Seminar Echtzeit-Rendering-Techniken

Sommersemester 2011

  •  Seminar Geovisualisierung

Wintersemester 2010/2011

  • Tutor Vorlesung Informationsvisualisierung
  • Seminar Advanced Visualization Techniques

Sommersemester 2010

  • Bachelorprojekt "Werkzeug zur Analyse umfangreicher Laser-Scans"

Wintersemester 2009/2010

  • Tutor Vorlesung Geovisualisierung
  • Bachelorprojekt "Werkzeug zur Analyse umfangreicher Laser-Scans"

Sommersemester 2009

  • Übung zur Vorlesung 3D Computergrafik