Computer Vision I: Variational Methods
WS 2016/17, TU München
Lecture
Location: Room 02.09.023
Time and Date:
Wednesday, 10.15h - 11.45h
Thursday, 10.15h - 11.00h
Lecturer: Prof. Dr. Daniel Cremers
The lectures are held in English.
Exercises
Location: Room 02.09.023
Time and Date: Monday, 9.15h - 11.30h
Organization: Thomas Möllenhoff, David Schubert
Retry Exam (Written)
Location: Room 5402.01.221K (CH 22210, Ivar-Ugi-Hörsaal)
Time and Date: Thursday, April 20, 2017, 16.00h-18.00h.
You may only use standard writing materials. No cheat sheet, no electronic devices.
There will be a post-exam review (Klausureinsicht) for the retake exam on Friday, April
28, 2017 in our lecture room 02.09.023 at 10am. Please bring
your student ID cards to identify yourselves.
Summary
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.
Prerequisites
The requirements for the class are knowledge in basic mathematics, in particular multivariate analysis and linear algebra. Some prior knowledge on optimization is a plus but is not necessary.
Lecture Material
Course material (slides and exercise sheets) can be accessed here.
Videos
Date of Lecture | Link |
---|---|
17.10.2013 | Video of Lecture 1 |
23.10.2013 | Video of Lecture 2 |
24.10.2013 | Video of Lecture 3 |
31.10.2013 | Video of Lecture 4 |
06.11.2013 | Video of Lecture 5 |
07.11.2013 | Video of Lecture 6 |
13.11.2013 | Video of Lecture 7 |
14.11.2013 | Video of Lecture 8 |
20.11.2013 | Video of Lecture 9 |
21.11.2013 | Video of Lecture 10 |
27.11.2013 | Video of Lecture 11 |
28.11.2013 | Video of Lecture 12a, Video of Lecture 12b |
11.12.2013 | Video of Lecture 13 |
18. & 19.12.2013 | Video of Lecture 14 |
08.01.2014 | Video of Lecture 15 |
09.01.2014 | Video of Lecture 16 |
16.01.2014 | Video of Lecture 17 |
22.01.2014 | Video of Lecture 18 |
23.01.2014 | Video of Lecture 19 |
30.01.2014 | Video of Lecture 20 |