183.280 Structural Pattern Recognition
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2020W, VO, 2.0h, 3.0EC


  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VO Lecture
  • Format: Hybrid

Learning outcomes

After successful completion of the course, students are able to enumerate the basic data structures and representations of structural pattern recognition: relations, graphs and graph pyramids, combinatorial maps, shape and context representations, formal and graph grammars, structure in motion, and topology and to justify the use of the related methodology with its pros and cons in selected applications.

Subject of course

Relations between patterns in space and time; representing structure: strings, arrays, trees, graphs, maps and grammars; shape and context, embedding in an n-dimensional space; distances on a given structure; graph spectra and eccentricity; operations on structures and among structures: recognition, parsing; exact and inexact matching; modification of structure under motion and tracking; topology and homology groups (nD holes, persistence); applications. For details see http://www.prip.tuwien.ac.at/Teaching/.

Teaching methods

Due to the imposed constraints of Covit19 papers, slides, and links will be provided in structured form. Then every student selects one of the topics and studies the provided material. As a result he produces a structured summary for the other students. Based on the studied topic he then chooses an application of the selected methodology. This part will be done in the exercises and should result in a scientific report that describes the problem, the selection of methods and the experimental evaluation. Interaction will be through email and file exchange but also small meetings may be organized to allow for efficient scientific discussions.

Mode of examination


Additional information

lecture: study of the selected material: 15h


specify problem 15h

design and select methodology 24h

evaluation concept 5h

illustrations 2h

report 14h



Examination modalities

- written and oral presentation (slides) of a self-chosen subproblem,

- jointly with the design and the selection of the methods for solving the problem, and

- evaluation and critical analysis of the results.

Course registration

Begin End Deregistration end
17.09.2020 00:00 11.10.2020 00:00 16.11.2020 00:00


Study CodeSemesterPrecon.Info
066 932 Visual Computing


No lecture notes are available.

Previous knowledge

Digital Image Processing, Pattern Recognition, basic mathematical concepts: order theory, relations;

data structures: strings, arrays, trees, graphs, fromal grammars.

Preceding courses

Accompanying courses