Computer Vision I: Variational Methods (IN2246)
Course 0000002737 in WS 2018/9
General Data
Course Type | lecture with integrated exercises |
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Semester Weekly Hours | 6 SWS |
Organisational Unit | Informatics 9 - Chair of Computer Vision and Artificial Intelligence (Prof. Cremers) |
Lecturers |
Daniel Cremers Björn Häfner Assistants: Marvin Eisenberger David Schubert |
Dates |
Tue, 10:00–12:00, Interims I 102 Wed, 10:30–12:30, Interims II 004 Thu, 10:00–12:00, Interims I 102 |
Assignment to Modules
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IN2246: Computer Vision I: Variational Methods / Computer Vision I: Variational Methods
This module is included in the following catalogs:- Catalogue of non-physics elective courses
Further Information
Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
additional remarks | Variational Methods are among the most classical techniques for optimization of cost functions in higher dimension. Many challenges in Computer Vision and in other domains of research can be formulated as variational methods. Examples include denoising, deblurring, image segmentation, tracking, optical flow estimation, depth estimation from stereo images or 3D reconstruction from multiple views. In this class, I will introduce the basic concepts of variational methods, the Euler-Lagrange calculus and partial differential equations. I will discuss how respective computer vision and image analysis challenges can be cast as variational problems and how they can be efficiently solved. Towards the end of the class, I will discuss convex formulations and convex relaxations which allow to compute optimal or near-optimal solutions in the variational setting. |
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Links | TUMonline entry |
Equivalent Courses (e. g. in other semesters)
Semester | Title | Lecturers | Dates |
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WS 2019/20 | Computer Vision I: Variational Methods (IN2246) | Cremers, D. Demmel, N. |
Tue, 10:00–12:00, Interims I 102 Thu, 10:00–12:00, Interims I 102 Wed, 10:30–12:30, Interims II 004 |