Computer Vision 2


WS 2022






Lecture Organization

The following information is preliminary and may change at a later date due to new regulations in the pandemic. We hope for your understanding.

  • The lecture will take place in presence. For this, we have reserved lecture halls with sufficient capacity to comfortably sit the expected number of participants with an extended distance (at least 1 empty seat between participants in all directions). If the number of registrations further increases beyond that capacity, we have the option to move to a larger lecture hall.

  • All lectures will be recorded as screencast and will be made available to all lecture participants as a video in the moodle learning room (typically 1-2 days after the lecture due to the postprocessing effort involved). This way, nobody will have to miss a lecture slot due to potential illness or quarantine periods. If none of those conditions apply, we however strongly recommend attending the lecture in person, as it makes for a more wholesome learning experience.

  • We will also experiment with transmitting the lecture as a live zoom broadcast from the lecture hall in the spirit of a true hybrid format, but it is unclear whether bandwidth will be sufficient to support this.

Lecture Description

The lecture will cover advanced topics in computer vision. A particular focus will be on state-of-the-art techniques for object detection, tracking, visual odometry and SLAM. There will be regular exercises accompanying the lecture.


In the last decades, Computer Vision has evolved into a rapidly growing field with research going into so many directions that no single book can cover them all. Some basic material can be found in the following books:

  • Computer Vision - A Modern Approach, D. Forsyth, J. Ponce, Prentice Hall, 2002
  • Multiple View Geometry, R. Hartley, A. Zisserman, 2nd edition, Cambridge University Press, 2003
  • An Invitation to 3D Vision, Y. Ma, S. Soatto, J. Kosecka, S. Sastry, Springer, 2003

However, a good part of the material presented in this class is the result of very recent research, so it hasn't found its way into textbooks yet. Wherever research papers are necessary for a deeper understanding, we will make them available on this web page.

Python Resources

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