Prof. Dr. Jürgen Döllner


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


Interaction and Locomotion Techniques for the Exploration of Massive 3D Point Clouds in VR Environments

Thiel, Felix; Discher, Sören; Richter, Rico; Döllner, Jürgen in Proceedings of ISPRS Technical Commission IV Symposium 2018 2018 .

Emerging virtual reality (VR) technology allows immersively exploring digital 3D content on standard consumer hardware. Using in-situ or remote sensing technology, such content can be automatically derived from real-world sites. External memory algorithms allow for the non-immersive exploration of the resulting 3D point clouds on a diverse set of devices with vastly different rendering capabilities. Applications for VR environments raise additional challenges for those algorithms as they are highly sensitive towards visual artifacts that are typical for point cloud depictions (i.e., overdraw and underdraw), while simultaneously requiring higher frame rates (i.e., around 90 fps instead of 30 - 60 fps). We present a rendering system for the immersive exploration and inspection of massive 3D point clouds on state-of-the-art VR devices. Based on a multi-pass rendering pipeline, we combine point-based and image-based rendering techniques to simultaneously improve the rendering performance and the visual quality. A set of interaction and locomotion techniques allows users to inspect a 3D point cloud in detail, for example by measuring distances and areas or by scaling and rotating visualized data sets. All rendering, interaction and locomotion techniques can be selected and configured dynamically, allowing to adapt the rendering system to different use cases. Tests on data sets with up to 2.6 billion points show the feasibility and scalability of our approach.
Weitere Informationen


  • 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)


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