Course detail

Computer Vision Applications

FEKT-NAPVAcad. year: 2019/2020

Not applicable.

Learning outcomes of the course unit

Not applicable.


Not applicable.


Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Sonka M., Hlavac V., Boyle R.: Image Processing, Analysis and Machine Vision. Thomson 2008. ISBN 978-0-495-08252-1. (EN)
Jahne B., Hausecker H., Geisler P.: Handbook of Computer Vision and Applications. Academic press 1999. ISBN 0-12-379770-5. (EN)

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Not applicable.

Language of instruction


Work placements

Not applicable.

Course curriculum

1. Special application in computer vision.
2. Cluster-based segmentation.
3. Local features and correspondences.
4. Region detector.
5. Region descriptors.
6. Global and combined descriptors.
7. Image understanding.
8. Distance and risk minimization classification.
9. Dynamic images.
10. Multiimage reconstruction.
11. Learning in recognition.
12. Selected passages of recognition.


Not applicable.

Classification of course in study plans

  • Programme EEKR-MN Master's

    branch MN-KAM , 1. year of study, summer semester, 5 credits, optional specialized

Type of course unit



26 hours, optionally

Teacher / Lecturer

Laboratory exercise

26 hours, compulsory

Teacher / Lecturer