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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

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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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Brief Bio

Ulrich Schlickewei studied Mathematics and Physics at the University of Freiburg i. Brsg., at the University of Rome "La Sapienza" and at the University of Paris VI. Following his Master's degree in Pure Mathematics from Paris University, Ulrich was a doctoral student at the Department of Mathematics of the University of Bonn under supervision of Prof. Dr. Daniel Huybrechts. In 2009 he received a Ph.D. for a thesis in the field of Complex Algebraic Geometry. Since October 2009, Ulrich has been a postdoctoral research fellow in the Computer Vision Group at the Technical University of Munich headed by Prof. Dr. Daniel Cremers.

Research Interests

My current research mainly focusses on the analysis of three-dimensional shapes. Recently we worked on orientation-preserving, elastic shape matching and on isometry-invariant feature detection.

The goal of shape matching is to register corresponding surface regions of two given three-dimensional shapes. This means for example to identify the hands, the feet and the head of two human figures. Once two shapes are registered, one can infer morphs between them. The video shows examples of such morphs, e.g. interpolating between a samba dancer and a hip hop dancer. In each of these example sequences, a registration of the first and the last shape has been computed, all intermediate frames are obtained by linear interpolation. The colors visualize regions which have been identified with each other.

Please refer to our project page for more information on this.

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