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Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich

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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:
CVG Group DVL Group

News

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

24.07.2020

Our practical course "Vision-based Navigation" (WS18, SS19) by Dr. Vladyslav Usenko and Nikolaus Demmel was honored as best practical course in the academic year 2018/2019 by the department for Informatics.

07.05.2020

We are organizing a workshop on Map-based Localization for Autonomous Driving at ECCV 2020, Glasgow, UK.

13.04.2020

Daniel Cremers received an ERC Advanced Grant (3.5 Mio Euro) for pioneering frontier research from the European Research Council. This constitutes his fifth ERC grant.

More



Computer Vision I: Variational Methods

WS 2017/18, TU München

News
Lecture

Location: Room 02.09.023
Time and Date:
Wednesday, 10.15h - 11.45h
Thursday, 10.15h - 11.00h
Lecturer: Dr. Yvain Queau

The lectures are held in English.

Exercises

Location: Room 02.09.023, also 02.05.014 for the practical part
Time and Date: Tuesday, 16:00h - 18:15h
Organization: Nikolaus Demmel, Christiane Sommer
Contact: cvvm-ws17@vision.in.tum.de
Office hour: Thursday, 11:00h - 12:00h, or upon request

In addition to the exercise session on Tuesday, the computer room 02.05.014 is reserved for you Thursdays 11:00h - 12:00h, right after the lecture. You can of course use it most other times, when there is not a different tutorial (see here for more info). Also, Thursdays 11:00h - 12:00h, Christiane and Nikolaus will be available for questions in their offices, so feel free to come by. You can also come by another time, but it probably best to write an email before.

Exam

Retake Exam Review

  • Date: 03.04.2018
  • Time: 14:00 - 16:00
  • Place: 02.09.023 (same room as lectures)

Please do not forget to bring your passport if you want to have a look at your exam!

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

Slides and exercise sheets can be accessed here.
For password request, please contact us using your TUM email address.

Videos

A previous (very similar) version of this course was recorded in 2013. The videos can be found here.

Rechte Seite

Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:
CVG Group DVL Group

News

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

24.07.2020

Our practical course "Vision-based Navigation" (WS18, SS19) by Dr. Vladyslav Usenko and Nikolaus Demmel was honored as best practical course in the academic year 2018/2019 by the department for Informatics.

07.05.2020

We are organizing a workshop on Map-based Localization for Autonomous Driving at ECCV 2020, Glasgow, UK.

13.04.2020

Daniel Cremers received an ERC Advanced Grant (3.5 Mio Euro) for pioneering frontier research from the European Research Council. This constitutes his fifth ERC grant.

More