Syllabus, Master's level, 1MD140
- Education cycle
- Second cycle
- Main field(s) of study and in-depth level
- Computational Science A1N, Computer Science A1N, Image Analysis and Machine Learning A1N
- Grading system
- Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Finalised by
- The Faculty Board of Science and Technology, 4 March 2021
- Responsible department
- Department of Information Technology
120 credits including a basic course in programming. Proficiency in English equivalent to the Swedish upper secondary course English 6.
On completion of the course, the student should be able to:
- describe the data flow in a visualisation system;
- outline the methods that transform the data and information to visual representations;
- use and program advanced software for various visualisation techniques;
- evaluate computer-generated visualisations by drawing upon principles and theories about the human visual system;
- select appropriate visualisation strategies and justify the chosen approaches.
The visualisation pipeline. Data representations and scalar visualisation. Vector and tensor visualisation. Multidimensional visualisation. Stereo Rendering. Perceptual issues in visualisation. Information Visualisation. Rendering techniques for visualisation such as volume rendering, splatting and isosurface generation.
The course includes projects using software for advanced visualisations.
Lectures, computer exercises and project work.
Written test (3 credits), compulsory assignments (2.5 credits), project (2 credits).
If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.
The course cannot be included in the same degree as 1TD389 Scientific Visualisation.