After successful completion of the course, students are able to understand the generation of 3D digital models and representations as a requirement for applying deep learning methods, and to analyze surface properties for running simulations. 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.

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, Procedural Modeling.

Lectures, excercises and paper presentations.

ECTS Breakdown (3 ECTS = 75 hours):

Lectures:
8 units of 1.5h each (approx. 12 hours)

Assignments (approx. 63 hours):
4 homework assignments with a load of approx. 51h
1 paper presentation with a load of approx. 12h

Course dates & timeline:
09.03.2021, 13:00-14:30 Introduction
16.03.2021, 13:00-14:30 Meshes, Assignment #1
23.03.2021, 13:00-14:30 Curves & Surfaces
13.04.2021, 13:00-14:30 Scan Pipeline, Assignment #2, Assignment #1 due
20.04.2021, 13:00-14:30 Applications 1
27.04.2021, 13:00-14:30 Applications 2, Assignment #3
11.05.2021, 13:00-14:30 Parametrization, Assignment #2 due
01.06.2021, 13:00-14:30 Procedural Modeling, Assignment #4
08.06.2021, 13:00-16:00 (depending) Paper presentations
22.06.2021 Assignments #3+#4 due

(Deadlines are always midnight)

Homework and a presentation with a total workload of approx. 63 hours.

Basic programming and math skills recommended (MATLAB, Python and linear algebra, calculus, differential equations will be used).