It is a classical problem in Machine Vision to represent, analyse and compare three-dimensional shapes. In the last years this field has known a fast development leading to a number of very powerful algorithms with a solid mathematical foundation. In this course we will present some of these, discussing both, the mathematics involved and the practical issues for the implementation.

Topics we plan to cover include:

• Foundations of Differential Geometry of curves and surfaces
• Matching pairs or a collection of shapes
• Classification of shapes
• Spectral methods (i.e. Laplace-Beltrami operators and their eigenspaces)
• Pointwise feature descriptors
• Machine learning applied to shape analysis

Location: Room 02.09.023
Time and Date: Tuesday 10:15 - 12:00, Thursday 14:00 - 15:45
Lecturer: Dr. Frank Schmidt, Matthias Vestner
Start: May, 2
The lecture is held in English.

Location: Room 02.09.023
Time and Date: Wednesday 14:00 - 16:00
Organization: Zorah Lähner
Start: May, 10

The excercise sheets consist of two parts:

1. Mathematics
2. Programming

You can submit your solutions via email to laehner@in.tum.de until tuesday (23:59) before the corresponding exercise class. Since we are not experts in decryption we ask you to hand in typewritten solutions for the first part and commented source code for the second part.

In the exercise class the solutions to the first part will be discussed.

The oral exam will be held in Room 02.09.023.
Please send an email to f.schmidt@in.tum.de with your 3 preferred slots.
First come first serve.

Course material (slides and exercise sheets) can be accessed here.

The password will be presented in the first lecture.