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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

We will cover the following fundamental topics:

1. challenge of machine vision (computer vision) and basics

2. image formation

3. basics of image processing

4. linear filters

5. sampling and multiscale image representations

6. basics of machine learning

7. neural architectures for computer vision

8. motion detection in videos

Optionally, some of the following topics are covered:

9. probabilistic models for computer vision

10. generative image models and representation learning

11. challenges in the use of machine learning methods for computer vision

12. geometry and computer vision

13. image-language models ((large) vision-language models)


Qualification Goals

The students

  • can explain basic concepts of computer vision such as object recognition, measurement and motion detection,
  • understand deep learning and its application to visual data,
  • know standard implementations of methods in computer vision and can use them,
  • can develop solutions to computer vision problems, and
  • are able to apply scientific working methods when independently recognizing, formulating and solving problems.

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

The module is assigned to Computer Science. Further information on eligibility can be found in the description of the study area.


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.