Computer Vision - Image Understanding - Bildverstehen
|Vorlesung:||Montag,||15.30 - 17.00, 1/346,||(Dr. J. Vitay)|
|Übung:||Dienstag,||15.30 - 17.00, 1/B202,||(A. Al Ali)|
|Übung:||Donnerstag,||11.30 - 13.00, 1/B202,||(A. Al Ali)|
Prerequisites: Modules in Mathematics I to IV, basic knowledge in Python.
Exam: written examination (90 minutes), 5 credit points.
Contact: julien dot vitay at informatik dot tu-chemnitz dot de.
Language: English. The written exam can of course be done in German.
Office hours: Mondays between 13:00 and 14:00 during the lectures period.
Exercises: start one week later: 17.10 and 19.10.
Note: there will be no exam in the summer semester 2018.
The course is an introduction to computer vision, from basic image processing (filters, Fourier transformation) to more advanced algorithms (object recognition, movement, facial features extraction).
- Image formation
- Image processing
- Geometric transformations
- Feature detection and matching
- Motion, optical flow
- Machine learning
The exercises are made on computers using the OpenCV computer vision library with the Python bindings.
The course is based primarily on the textbook by Richard Szeliski:
Richard Szeliski (2010). Computer Vision: Algorithms and Applications. Springer.
A free online draft is available at szeliski.org/Book/
The online book by Simon Prince, Computer vision: models, learning and inference (available at computervisionmodels.com) might also be helpful.
Slides for the lecturesChapter 01 - Introduction (pdf)
Chapter 02 - Image Formation (pdf)
Chapter 03 - Image processing (pdf)