Hasso-Plattner-Institut
Prof. Dr. Jürgen Döllner
  
 

Contact

Sören Discher

Tel.: +49-(0)331 5509-3905
Fax: +49-(0)331 5509-172
Room: H-2.14
Email: soeren.discher(at)hpi.de

Research Gate

 

Research Interests

  • Rendering and Interaction Techniques for Semantically Rich 3D Point Clouds
  • Scalable Rendering of Non-Static 3D Point Clouds
  • Real-Time Compression and Decompression for 3D Point Clouds
  • Geospatial Virtual Reality

Publications

A Scalable WebGL-based Approach for Visualizing Massive 3D Point Clouds using Semantics-Dependent Rendering Techniques

Discher, Sören; Richter, Rico; Döllner, Jürgen in Proceedings of Web3D ’18 2018 .

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.
A Scalable WebGL-based Ap... - Download
A Scalable WebGL-based Ap... - Download
A Scalable WebGL-based Ap... - Download
A Scalable WebGL-based Ap... - Download
Weitere Informationen
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Talks

  • Interaction and Locomotion Techniques for the Exploration of Massvie 3D Point Clouds in VR Environments - held at the ISPRS TC IV Mid-term Symposium “3D Spatial Information Science – The Engine of Change”, Delft, The Netherlands (10/2018)
  • A Scalable WebGL-based Approach for Visualizing Massive 3D Point Clouds using Semantics-Dependent Rendering Techniques - held at the Web3D ’18, Poznan, Poland (06/2018)
  • A Point-Based and Image-Based Multi-Pass Rendering Technique for Visualizing Massive 3D Point Clouds in VR Environments - held at the WSCG 2018, Plzen, Czech Republic (05/2018)
  • Applications, Challenges and Solutions for 4D Point Clouds - held with Rico Richter at the International LiDAR Mapping Forum 2017, Denver, CO, USA (02/2017)
  • 3D Point Clouds for the Preservation and Documentation of Cultural Heritage - held at the HPI UCT Spring Workshop 2016, Cape Town, South Africa (04/2016)
  • Visualization and Interaction Techniques for Massive, Semantically Rich 3D Point Clouds - held at the Capturing Reality Forum, Salzburg, Austria (11/2015)
  • Interactive and View-Dependent See-Through Lenses for Massive 3D Point Clouds - held at the 3D GeoInfo 2015, Kuala Lumpur, Malaysia (10/2015)
  • Scalable Visualization of Massive 3D Point Clouds - held at the HPI UCT Spring Workshop 2015, Cape Town, South Africa (04/2015)
  • Echtzeit-Rendering-Techniken für 3D-Punktwolken basierend auf semantischen und topologischen Attributen - held at the 35. Wissenschaftlich-Technische Jahrestagung der DGPF, Cologne, Germany (03/2015)
  • Konzepte für eine Service-basierte Systemarchitektur zur Integration, Prozessierung und Analyse von massiven 3D-Punktwolken - held at the 34. Wissenschaftlich-Technische Jahrestagung der DGPF, Hamburg, Germany (03/2014)

Teaching

Winter 2019/20

  • Course Advanced Point Cloud Analytics (tutor)
  • Bachelor project Deep Learning for 3D Infrastructure Data

Summer 2019

  • Course Selected Topics in Visual Computing (tutor)
  • Bachelor project Deep Learning for Geospatial Data

Winter 2018/19

  • Course Visualization Algorithms and Techniques (tutor)
  • Bachelor project Deep Learning for Geospatial Data

Summer 2018

  • Seminar Games of Life (tutor)
  • Seminar Advanced Games of Life (tutor)
  • Seminar Selected Topics in Spatial Analytics (tutor)
  • Bachelor project Web Platform for 3D Point Clouds

Winter 2017/18

  • Seminar Geovisualisierungstechniken (tutor)
  • Bachelor project Web Platform for 3D Point Clouds

Summer 2017

  • Seminar Advanced Information Visualization (tutor)
  • Bachelor project Geospatial Virtual Reality

Winter 2016/17

  • Seminar Processing and Visualization of 3D Geodata (tutor)
  • Bachelor project Geospatial Virtual Reality

Summer 2016

  • Seminar Methods and Techniques of Geospatial Visualization (tutor)
  • Bachelor project The Point Cloud

Winter 2015/16

  • Seminar Point Cloud Analytics (tutor)
  • Bachelor project The Point Cloud

Summer 2015

  • Lecture Einführung in die Programmiertechnik II (tutor)
  • Seminar Spatial Analytics (tutor)
  • Bachelor project 3D Point Clouds: Big Spatial Data

Winter 2014/15

  • Lecture Computer Graphics II (tutor)
  • Lecture Geoinformation Technologies (tutor)
  • Seminar Geovisualization (tutor)
  • Bachelor project 3D Point Clouds: Big Spatial Data

Summer 2014:

  • Lecture Computer Graphics I (tutor)
  • Seminar Information Visualization (tutor)
  • Bachelor project Analysis and Visualization of 3D Point Clouds

Winter 2013/14:

  • Seminar Game Programming (tutor)
  • Bachelor project Analysis and Visualization of 3D Point Clouds