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Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich

Home Teaching Summer Semester 2019 Computer Vision II: Multiple View Geometry (IN2228)

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Computer Vision II: Multiple View Geometry (IN2228)

SS 2019, TU München


If you plan to attend, please register for the course in TUMonline.
Later during the semester you will have to register for the exam.


Location: Room 02.09.023
Time and Date:

Lecturer: Prof. Dr. Daniel Cremers

The lecture is held in English.


Location: Interims Hörsaal 1 (5620.01.101)
Time and Date:
Organization: Mohammed Brahimi, David Schubert
(If you have any questions please email to: mvg-ss19@vision.in.tum.de)

Exercises are split into a theoretical and a practical part. Due to the high number of students, the practical part of the tutorial will also take place in the Interims Hörsaal, which requires students to bring a laptop. If this is not possible, students can also use the computers in room 02.05.014, which is reserved during the tutorial, but can be used at any other time if there are free computers. Don't forget to get login credentials from the tutors in case you are planning to do so.


The programming exercises are done in MATLAB. You don't need extensive prior MATLAB knowledge. If you have never used MATLAB before, we recommend following a basic tutorial. Please install MATLAB on your laptop before the first exercise using the university's student licenses.

Note on MATLAB version:

We suggest you to use a MATLAB version 2016b or later. For the solutions we make use of function definitions inside Matlab script files. This feature was added only in 2016b. So if you have an earlier version, we suggest you to upgrade (alternatively you can move all function definitions to separate files). See also https://de.mathworks.com/help/matlab/matlab_prog/local-functions-in-scripts.html.


The lecture introduces the basic concepts of image formation - perspective projection and camera motion. The goal is to reconstruct the three-dimensional world and the camera motion from multiple images. To this end, one determines correspondences between points in various images and respective constraints that allow to compute motion and 3D structure. A particular emphasis of the lecture is on mathematical descriptions of rigid body motion and of perspective projection. For estimating camera motion and 3D geometry we will make use of both spectral methods and methods of nonlinear optimization.

Lecture Material

Slides and exercises can be downloaded here. We will provide the password in the tutorial sessions. Alternatively, for password requests, please contact us using your TUM email address.

Lecture Videos

Yi Ma, Stefano Soatto, Jana Kosecka, Shankar S. Sastry. An Invitation to 3-D Vision

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Informatik IX
Chair for Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching