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| Detailed information |
| Original study plan |
Master's programme Computer Science 2025W |
| Learning Outcomes |
Competences |
| Students are familiar with the basics of Computer Vision and its links to machine learning approaches. They understand its applications in domains such as 3D reconstruction, robotics, medical engineering, media technology, automatization, biometry, human-computer interaction, contact free measurement, remote sensing, quality control, etc.
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| Skills |
Knowledge |
Basic understanding of:
- Calibration of and capturing images with digital cameras (optics, sensorics, math. camera model) (K4,K5)
- Processing images in different domains (spatial, frequency, gradient) (K4,K5)
- Model-based vs. learning-based approaches to computer vision (K4,K5)
- Higher-level applications of computer vision to tasks such as classification, segmentation, tracking, and 3D reconstruction (K4,K5)
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- Capturing Digital Images
- Digital Image Processing
- Machine Learning
- Feature Extraction
- Segmentation
- Optical Flow
- Object Detection
- Camera Calibration
- 3D Vision
- Trends in Computer Vision
- Basic knowledge in machine learning required
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| Criteria for evaluation |
eExam (Moodle test), physical presence is required
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| Methods |
Online only (Zoom), recordings, slides.
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| Language |
English |
| Study material |
- Computer Vision: Algorithms and Applications, Richard Szeliski, Springer, ISBN: 1848829345, 2010
- Computer Vision – A Modern Approach, Forsyth and Ponce, 2nd edition, Addison Wesley, ISBN-10: 013608592X, 2011
- Multiple View Geometry in Computer Vision, Hartley and Zisserman, 2nd edition, Cambridge Press, ISBN: 0521540518, 2003
- Pattern Classification, Duda, Hart, and Stork, 2nd edition, Wiley-Interscience, ISBN: 978-0-471-05669-0, 2000
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| Changing subject? |
No |
| Further information |
This lecture and the associated lab form an inseparable didactic unit. The learning outcomes presented here are achieved through the combined effect of the two courses.
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| Corresponding lecture |
in collaboration with 921PECOCOVU20: UE Computer Vision (1.5 ECTS) equivalent to
921PECOCOVK13: KV Computer Vision (4.5 ECTS)
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