Data driven Methods for 3D Shape Analysis
Semester: |
SS 2021 |
Type: |
Lecture |
Lecturer: |
|
Credits: |
ECTS 6 (V3/Ü2) |
Contact: |
shapeanalysis@cs.rwth-aachen.de |
Note: This page is for a course from a previous semester.
Find a list of current courses on the Teaching page.
Find a list of current courses on the Teaching page.
Type |
Date |
Room |
|---|---|---|
| Lecture | Tue, 14:30-16:00 | Zoom |
| Lecture | Thu, 14:30-16:00 | Zoom |
| Tutorial | Wed, 16:30-18:00 | Zoom |
Online course will be held using Zoom. Please register for the lecture via RWTHonline to get access to the Moodle Course Room where you can find the link to the Zoom Meeting Room.
- The first lecture is on Thursday, April 15
- The first tutorial is on Wednesday, April 21
Contents
The lecture covers the following topics:
- Clustering
- Dimensionality Reduction
- Global and Local Shape Descriptors
- Shape Structures
- Distance Measures
- Surface Maps
- Learning based approaches for Shape Encoding
- Learning based approaches for Shape Decoding
- Generation of novel Shapes
Organizational
- Weekly exercises (mandatory practical, optional theoretical)
- Practical part in python
- 120 minutes exam
- Exam admittance requires 50% of practical exercise points
- Small exam bonus for 75% of practical exercise points
Prerequisites
- The lecture "Basic Techniques in Computer Graphics" is recommended but not a hard requirement
- The lecture "Geometry Processing" is considered helpful, but also not required.
