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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



Lecture: Robotic 3D Vision (3h +1h, 5ECTS)

WS 2020/21, TU München

Lecture

Time and Date:
Wednesday (every week), 14.00h - 15.30h online (starting from Nov 4th)
Friday (every second week), 14.00h - 15.30h online

Lecturer: Dr. Niclas Zeller

The lectures are held in English.

Exercises

TBD ..

Study programme: M. Sc. Informatics

Exam date: TBD…

Registration

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

Summary

This lecture will cover vision-based approaches to 3D robotic perception such as 3D simultaneous localization and mapping or 3D object detection with monocular, stereo and RGB-D cameras. Vision-based approaches attract significant attention in research and industrial applications due to the cost-effectiveness of passive cameras but also RGB-D cameras in comparison to sensors such as lasers or radars. The course will treat the following topics:

  • Multi-view geometry
  • Probabilistic filtering
  • Non-linear least squares optimization
  • Indirect and direct methods for rigid image alignment
  • Visual odometry, indirect and direct methods
  • Visual-inertial odometry
  • Visual SLAM, pose graph optimization
  • 3D map representations
  • 3D object detection and tracking
Prerequisites

Passion for solving complex computer vision problems. A solid background in basic mathematics such as linear algebra and analysis is required. Background in basics of multi-view geometry (f.e. acquired through successful participation in the lecture “Computer Vision II: Multi-View Geometry” (IN2228)) is recommended. The course will include exercises for which previous knowledge in programming with Python and Matlab will be required.

Lecture Material

Will be made available.

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