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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

10.12.2020

Frank Dellaert (Georgia Tech) will give a talk in the TUM AI lecture series on Dec 17th, 4pm! Livestream

15.10.2020

Jon Barron (Google) will give a talk in the TUM AI lecture series on Oct 22nd, 9pm! Livestream

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.

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

WS 2020/21, TU München

News

16.01.2021 Exercise Sheet 5 is now available on the course webpage.
13.01.2021 Solutions for Exercise Sheet 4 are now available.
28.12.2020 Exercise Sheet 4 is now available on the course webpage.
25.12.2020 Solutions for Exercise Sheet 3 are now available on the course webpage.
06.12.2020 Exercise Sheet 3 and solutions for Exercise Sheet 2 are now available on the course webpage.
22.11.2020 I've set up a Moodle for associated with this course. Please feel free to ask there any related questions. Moodle
22.11.2020 Exercise Sheet 2 and solutions for Exercise Sheet 1 are now available on the course webpage.
09.11.2020 Exercise Sheet 1 is available on the course webpage.

Lecture

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

Lecturer: Dr. Niclas Zeller

The lectures are held in English.

Exercises

Time and Date:
Friday (every second week, alternating with lecture), 14.00h - 15.30h online (starting from Nov 13th)
Organizer/Tutor: Patrick Wenzel

Study programme: M. Sc. Informatics

Exam date: 24.02.2021, 14:15 - 15:45

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

All lecture and exercise material will be made available 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

10.12.2020

Frank Dellaert (Georgia Tech) will give a talk in the TUM AI lecture series on Dec 17th, 4pm! Livestream

15.10.2020

Jon Barron (Google) will give a talk in the TUM AI lecture series on Oct 22nd, 9pm! Livestream

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.

More