186.191 Realtime Visualization
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2022W, VU, 2.0h, 3.0EC


  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise
  • Format: Hybrid

Learning outcomes

After successful completion of the course, students are able to understand and implement advanced real-time visualization concepts. They are able to design and implement interactive systems to visually analyze large and complex data, such as large volume data sets with real-time illumination, noisy ultrasound data, very large networks, data tables, or 4D simulation data.

Subject of course

The lecture part of the course covers advanced theoretical concepts for processing and visualizing large data in real-time, such as high-performance computing, in-situ visualization, GPGPU for real-time visualization, and real-time interactive web-based information visualization. The lectures will also present state-of-the-art real-time visualization applications, such as real-time volume illumination, real-time visualization and filtering of ultrasound data, real-time visualization of large graphs, and real-time simululation and visualization for flood management. The lecture will be organized by Manuela Waldner. Further lecturers are Peter Mindek, Renata Raidou, and Daniel Cornel.

The practical part of the course introduces advanced programming for interactive real-time visualization of large data utilizing modern graphics hardware concepts (shaders, GPGPU). The lab is organized by Aron Kovacs.

The lecture zoom links, lecture recordings, and all lecture and lab material can be found on TUWEL. Lectures take place Thursdays 11a.m. (c.t.) in Favoritenstraße 9-11, 5th floor. 

Teaching methods

Lectures with slides. Programming exercises (real-time visualization project).

Mode of examination


Additional information

ECTS breakdown:  3 ECTS = 75 hours

37.5 hours - implementation, presentation, and documentation of the lab assignment

37.5 hours - lecture attendance and preparation for oral exam



Course dates

Thu11:00 - 13:0006.10.2022 - 26.01.2023Seminarraum FAV 05 (Seminarraum 186) (LIVE)Lecture
Realtime Visualization - Single appointments
Thu06.10.202211:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu13.10.202211:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu20.10.202211:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu27.10.202211:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu03.11.202211:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu10.11.202211:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu17.11.202211:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu24.11.202211:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu01.12.202211:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu15.12.202211:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu22.12.202211:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu12.01.202311:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu19.01.202311:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture
Thu26.01.202311:00 - 13:00Seminarraum FAV 05 (Seminarraum 186) Lecture

Examination modalities

Oral examination, project presentations, and submission interview.

Course registration

Begin End Deregistration end
08.09.2022 00:00 16.10.2022 00:00 01.11.2022 00:01


Study CodeObligationSemesterPrecon.Info
066 645 Data Science Not specified
066 932 Visual Computing Mandatory elective


No lecture notes are available.

Previous knowledge

Visualization knowledge and OpenGL programming skills