Basic Mathematical Tools for Imaging and Visualization
Course with lectures and exercises for Master students (IN2124).
- Lectures: Tobias Lasser
- Exercises: Theodor Cheslerean-Boghiu, Josue Page Vizcaino, Erdal Pekel
- chat platform https://zulip.in.tum.de, stream #BMT
- Lectures: Mondays, 16:15 - 17:45, Interims I Hörsaal 2 (5620.01.102)
- additional live-stream and recordings via TUM Live
- Exercises: Wednesdays, 15:30 - 17:00, MW 1801 (5508.02.801)
- additional live-stream via BBB (no recordings)
- introductory session: Oct. 19, 2022, 15:30 - 17:00, MW 1801 and via TUM Live
- first regular course week: starting Oct. 24, 2022
- endterm: Feb. 15, 2023, 8:00 - 9:15 (MW 2001, Hörsaal im Galileo, Hörsaal EI)
- retake: Apr. 14, 2023, 11:00 - 12:15 (MI HS 1)
For the development and application of many image processing techniques and computer vision algorithms, including deep learning, a deep mathematical understanding is of fundamental importance. This course aims to provide interested students with a solid mathematical basis for imaging and visualization applications.
Basic and most commonly applied techniques will be presented in the lectures and demonstrated in example applications from Image Processing and Computer Vision. The same mathematical methods are also applied in other engineering disciplines such as artificial intelligence, machine learning, computer graphics, robotics etc. The course is covering topics ranging from linear algebra, analysis, and optimization to probability theory.
All course materials will be available via Moodle (access restricted to course participants, registration via TUMonline).