Visual Computing (M.Sc.)

Visual perception is responsible for most our impressions about the world around us. This is why computers are being increasingly used to process digital images and visual simulations. Areas in which these applications are already well established include medical technology, the automotive industry, multimedia systems and industrial quality control. Creating and analysing digital images requires specialist knowledge. The Master's degree programme "Visual Computing" at Saarland University is therefore a joint undertaking involving the university departments of Informatics and Computer Science, Mathematics and Mechatronics, the medical technology division at the Fraunhofer Institute for Biomedical Engineering and the Max Planck Institute for Informatics. The programme also maintains close cooperative ties with the Max Planck Institute for Software Systems, the German Research Center for Artificial Intelligence and the Fraunhofer Institute for Nondestructive Testing, which is also located on the Saarbrücken campus.

Description

The M.Sc. programme "Visual Computing" teaches students the fundamental principles, processes and applications of computer-assisted processing of visual information. Students will become acquainted with the theory and practice of image analysis and pattern recognition. They learn how images are generated, processed and analysed from a technical point of view, and how to create static and animated images that are the best possible representation of reality. The requisite theoretical and practical knowledge is taught in courses and modules that cover image generation and the underlying geometrical principles, image synthesis and image analysis and related areas. Students on the Master's programme also acquire important fundamental knowledge in the disciplines of mathematics, informatics, physics and mechatronics.

English is the language of instruction and examination. Particularly talented students are eligible for scholarships from the International Max Planck Research School for Computer Science. Graduates from the Saarbrücken Master's programme not only have an excellent foundation from which to undertake subsequent doctoral research work, they also have excellent career prospects in a wide range of fields, including the optical industry, the medical technology sector, bioinformatics, the automotive industry, telecommunications, industrial quality control, multimedia, media design and robotics.

Structure

The degree programme is composed of lectures and seminars. Some of the lecture courses have accompanying tutorials or problem-solving classes. Students are also required to compile and submit a Master's thesis.

Taught courses conclude with an assessment of student learning, which is usually graded. Credits gained from assessments are cumulative and contribute to the student's overall academic achievement. Information on the type and duration of the academic assessment for each course can be found in the module catalogue.

To complete the Master's programme, students must accumulate 90 credits (90 CP) from taught courses and 30 credits from the Master's thesis project in their final semester. The standard period of study for the M.Sc. programme is four semesters, with students typically accumulating 30 credits per semester.

The programme includes at least the following modules:*)

Core areas in visual computing

1. Imaging techniques and geometric principles

  • Introduction to Image Acquisition Methods, 4 CP (V2)
  • Medical Imaging, 9 CP (V4 Ü2, Mathematics)
  • Imaging Techniques: Sonography and X-ray Imaging 4 CP (V2, medical engineering, annual)
  • Imaging Methods: MRI, 5 CP (V2 Ü1, medical engineering, annual)
  • Geometric Modelling, 9 CP (V4 Ü2) (at least every two years)
  • Effective Computational Geometry for Curves and Surfaces, 6 CP (V4)

2. Image analysis

  • Image Processing and Computer Vision, 9 CP (V4 Ü2) (at least every two years)
  • Pattern and Speech Recognition, 6 CP (V2 Ü2) (Mechatronics, at least every two years)
  • Pattern Recognition, 5 CP (V2 Ü1)
  • Differential Equations in Image Processing and Computer Vision, 9 CP (V4 Ü2)
  • Differential Geometric Aspects of Image Processing, 4 CP (V2)
  • Probabilistic Methods in Image Processing, 4 CP (V2)
  • Mathematical Morphology in Image Analysis, 4 CP (V2)
  • 3D Image Analysis and Synthesis, 6 CP (V2 Ü2)

3. Image synthesis

  • Computer Graphics, 9 CP (V4 Ü2) (at least every two years)
  • Computer Graphics 2, 9 CP (V4 Ü2)
  • Scientific Visualization, 9 CP (V4 Ü2) (at least every two years)
  • Multimedia, 6 CP (V2 Ü2)
  • 3D Image Analysis and Synthesis, 6 CP (V2 Ü2)

4. Seminars covering a range of topics in the field of visual computing, 8 CP. These seminars are offered every semester.

Related fields in informatics and other disciplines

  • Information Retrieval and Data Mining, 9 CP (V4 Ü2)
  • Artificial Intelligence, 9 CP (V4 Ü2)
  • Telecommunications I/Digital Transmission and Signal Processing, 9 CP (V4 Ü2)
  • Telecommunications II/Audio/Visual Communication & Networks, 9 CP (V4 Ü2)

These lecture courses are offered at least once every two years.

Additional modules that may be offered include:

  • Advanced modules and special courses related to the lectures listed above
  • Modules in the areas of machine learning and robotics
  • Modules in language recognition and computer linguistics
  • Modules in the field of medical engineering

Supplementary modules covering important fundamentals in other fields

These modules allow students to address specific gaps in their knowledge of important fundamental fields, such as:

  • Mathematics (modules offered include: Practical Mathematics, Theory and Numerical Methods of Solving Ordinary Differential Equations, Stochastics, Numerical Methods of Solving Partial Differential Equations, Integral Equations, Calculus of Variations, Differential Geometry of Curves and Surfaces, Partial Differential Equations, Inverse Problems, Integral Transformations)
  • Informatics (modules offered include: Programming 1 and 2, Software Lab Course, Software Engineering, Algorithms and Data Structures, Optimization)
  • Mechatronics (modules offered include: Fundamentals of Signal Processing, Digital Signal Processing)
  • Physics (modules offered include: Introduction to Physics I and II or Physics for Engineers I and II)

These modules are offered at least once every two years.

Additional credits

Students can acquire further credits by taking additional modules (other than those listed above, such as language courses, modules in visual culture and communication in the arts, media design, cognitive science, psychology, etc.) or by supervising undergraduates in tutorials or problem-solving classes.

*)
V = Vorlesung (lecture course)
Ü = Übung (tutorial or problem-solving class)
S = Seminar (seminar)

The numeral immediately behind one of the above abbreviations represents the number of contact hours per week. For example, 'V4 Ü2' means that for this particular module students have 4 hours of lectures a week and a 2-hour tutorial or problem-solving class.

Additional information

The Master's programme can be studied either part time or full time. Students must study full time when working on their Master's thesis in the final semester. More information is available on the Part-time studies website (available in German only).

Particularly talented students are eligible for scholarships from the International Max Planck Research School (IMPRS). Students who have been accepted for the Master's programme in Visual Computing will be automatically considered for a scholarship. No separate application is required.

English language courses and a course teaching German as a foreign language are offered by the Max Planck Institute for Informatics (MPII). Additional language courses are offered by the International Office and the Language Centre at Saarland University. Students can earn up to 6 credits towards their Master's degree from language courses.

Requirements & application

Admission requirements

In order to be admitted to the programme, students must have received a Bachelor's degree or equivalent qualification from a German or foreign university in the field of Visual Computing or a related field (particularly informatics, computer science, mathematics, physics, electrical engineering or mechatronics) or proof of equivalent academic achievement.

Specifically, they must also provide the following information and/or documents:

  • Proof of previous academic qualifications (school and higher education)
  • A dossier or a qualified letter of reference that demonstrates the student's particular interest in the M.Sc. programme
  • Details about relevant work/study periods abroad and relevant work experience or internships
  • Proof of advanced proficiency in English

How to apply

Information about application and admission procedures can be found on the dedicated programme webpages.

 

Regulations

At a glance

Standard period of study4 semesters for full-time students
Part-time studies are possible
Language of instructionEnglish
English language requirementsAdvanced level
Restricted entryNo
Application deadlineWinter semester: 15 May
Summer semester: 15 November
Tuition feesNot applicable
Semester feeSee current fee structure
Web pageWebsite of the Master programme

Contact

Course adviser

Study Coordination
of Computer Science
Frau Dr.in Rahel Stoike-Sy
Frau Barbara Schulz-Brünken
Saarland Informatics Campus
Building E1 3, R.R.207-209
66123 Saarbrücken

master(at)cs.uni-saarland.de

Saarland Informatics Campus

Central Student Advisory Service

Saarbrücken Campus
Building A4 4, Ground floor
Phone: +49 681 302-3513
studienberatung(at)uni-saarland.de
www.uni-saarland.de/studienberatung

Central Student Advisory Service

Saarbrücken Campus
Building A4 4, Ground floor
Phone: +49 681 302-3513
studienberatung(at)uni-saarland.de

Central Student Advisory Service

Accredited study programmes

Saarland University was one of the first universities in Germany to achieve Quality Assurance Accreditation and has held the Accreditation Council’s official quality mark continuously since 2012.

Quality management