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.
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, Aleksandr Amirkhanov, 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.).
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
