Instructors: Prof. Dr. Simone Frintrop
Event type:
Lecture
Displayed in timetable as:
CV 1 - VL
Hours per week:
2
Language of instruction:
English
Min. | Max. participants:
- | 40
Comments/contents:
The field of Computer vision deals with developing algorithms that interpret and modify images. This lecture offers an introduction into the methods of computer vision, with a focus on the following topics:
- the human visual system and its implications for computer vision
- basics of digital images
- basics of image processing
- convolution and digital filters
- edge and line detection
- segmentation
- features and interest points
- classification of objects and scenes (e.g. deep learning for computer vision)
The lecture takes place every winter semester
Learning objectives:
Knowledge of the basics of computer vision methods as a basis for application areas such as
Image retrieval and image search engines
Human computer interaction
Object- and scene recognition
Monitoring and surveillance
Robotics
Didactic concept:
Lecture (in English).
Literature:
R. Klette: Concise Computer Vision: An Introduction into Theory and Algorithms, Springer 2014
R.C. Gonzalez, R.E. Woods: Digital Image Processing (4th edition), Prentice-Hall 2017
R. Szeliski, Computer Vision: Algorithms and Applications, Springer, 2011
D.A. Forsyth, J. Ponce: Computer Vision, A Modern Approach (2nd edition), Prentice-Hall 2012
(additional literature will be announced during the lecture)
Additional examination information:
There will be a written exam at the end of the term.
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