Aim and Subject

The goal is to provide a solid understanding of how 3D digital models are generated and represented as a requirement for applying deep learning methods and analyzing surface properties for running simulations. Deep learning with 3D data, reconstruction from images or sensors, simulations on surfaces, and procedural modeling: In this course, you will practice processing meshes with machine learning algorithms, run simulations, and generate entire cities procedurally.

The following topics will be treated in this course among others: Polygonal Meshes, Curves and Surfaces Representations and Properties, Reconstruction of 3D Models from Scans, Parametrization, Simulations on Surfaces, and Procedural Modeling

Time and Place

Usually* Tuesdays 13:00-14:30 in the Seminar room FAV 05 (Favoritenstrasse 9, Stiege I, 5th Floor, room HA0503).

*except introduction and lecture on 18.04., which is already at 10:00-12:00 and in FAV 01A (Favoritenstrasse 9, Stiege I, 1st floor, room HE0102).

Schedule for the course 2023

*Thursday 09.03.2023, 15:30-17:00 Introduction

for the remaining lecture dates please see the TISS-Page.

Communication

The announcements and discussion forums, as well as information regarding the assignments, are available on the TUWEL-Page.

For any urgent or other communication, please contact the organizer of the course, Stefan Ohrhallinger.