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CS 657 — Computer Vision I
(dt. Computer Vision I)

Level, degree of commitment Specialization module, compulsory elective module
Forms of teaching and learning,
workload		 Lecture (2 SWS), recitation class (2 SWS),
180 hours (60 h attendance, 120 h private study)
Credit points,
formal requirements		 6 CP
Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises as well as at least 2 presentations of the tasks.
Examination type: Oral examination (individual examination) or written examination
Language,
Grading		 English,
The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Computer Science.
Duration,
frequency		 One semester,
each winter semester
Person in charge of the module's outline Prof. Dr. Ralph Ewerth

Contents

Translation is missing, sorry. German original:

Wir werden folgende grundlegende Themen behandeln:

1. Herausforderung des maschinellen Sehens (Computer Vision) und Grundlagen

2. Bildentstehung

3. Grundlagen der Bildverarbeitung

4. Lineare Filter

5. Abtastung und multiskalige Bilddarstellungen

6. Grundlagen des maschinellen Lernens

7. Neuronale Architekturen für Computer Vision

8. Bewegungserkennung in Videos

Optional werden einige der folgenden Themen behandelt:

9. Probabilistische Modelle für Computer Vision

10. Generative Bildmodelle und Repräsentationslernen

11. Herausforderungen bei der Nutzung maschineller Lernverfahren für Computer Vision

12. Geometrie und Computer Vision

13. Bild-Sprach-Modelle ((large) vision-language models)


Qualification Goals

Translation is missing, sorry. German original:

Die Studierenden

  • können grundlegende Konzepte der Computer Vision wie Objekterkennung, Vermessung und Bewegungserfassung erläutern,
  • verstehen Deep Learning und dessen Anwendung auf visuelle Daten,
  • kennen Standardimplementierungen von Methoden in der Computer Vision und können diese einsetzen,
  • können Lösungen zu Problemen der Computer Vision erarbeiten, und
  • sind in der Lage, wissenschaftliche Arbeitsweisen beim eigenständigen Erkennen, Formulieren und Lösen von Problemen anzuwenden.

Prerequisites

None. The competences taught in the following modules are recommended: Object-oriented Programming, either Algorithms and Data Structures or Practical Informatics II: Data Structures and Algorithms for Pre-Service-Teachers, System Software and Computer Communication, either Declarative Programming or Concepts of Programming Languages for Pre-Service-Teachers.


Applicability

Module imported from M.Sc. Computer Science.

It can be attended at FB12 in study program(s)

  • B.Sc. Data Science
  • B.Sc. Computer Science
  • M.Sc. Data Science
  • M.Sc. Computer Science
  • M.Sc. Mathematics
  • M.Sc. Business Informatics

When studying B.Sc. Data Science, this module can be attended in the study area Free Compulsory Elective Modules.


Recommended Reading

  • Torralba, Antonio, Phillip Isola, & William T. Freeman (2024). Foundations of Computer Vision. MIT Press.
  • Szeliski, Richard (2022). Computer Vision: Algorithms and Applications. Springer Nature.
  • Burger, Wilhelm & Burge, Mark. J. (2022). Digital Image Processing: An Algorithmic Introduction. Springer Nature.



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2025/26. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

  • Winter 2016/17 (no corresponding element)
  • Summer 2018 (no corresponding element)
  • Winter 2018/19 (no corresponding element)
  • Winter 2019/20 (no corresponding element)
  • Winter 2020/21 (no corresponding element)
  • Summer 2021 (no corresponding element)
  • Winter 2021/22 (no corresponding element)
  • Winter 2022/23 (no corresponding element)
  • Winter 2023/24 (no corresponding element)
  • Winter 2025/26

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.