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Advanced Optical Technologies (Master of Science) >>
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Computer Vision (CV)- Lecturers
- Prof. Dr. Bernhard Egger, Prof. Dr.-Ing. habil. Andreas Maier, Prof. Dr. Tim Weyrich
- Details
- Vorlesung
2 cred.h, ECTS studies, ECTS credits: 2,5
nur Fachstudium, Sprache Englisch
Time and place: Thu 12:15 - 13:45, H4
- Fields of study
- WPF ME-BA-MG6 4-6
WPF INF-MA ab 1
WF ICT-MA-MPS ab 1
WF CME-MA ab 1
WPF AI-MA ab 1
WPF ME-MA-MG6 1-3
- Contents
- This lecture discusses important algorithms from the field of computer vision. The emphasis lies on 3-D vision algorithms, covering the geometric foundations of computer vision, and central algorithms such as stereo vision, structure from motion, optical flow, and 3-D multiview reconstruction. The course will also introduce Convolutional Neural Networks (with some examples to play around) and discuss it's importance and impact. Participants of this advanced course are expected to bring experience from prior lectures either from the field of pattern recognition or from the field of computer graphics.
- Recommended literature
- Richard Szeliski: Computer Vision: Algorithms and Applications, Springer 2011.
Richard Hartley and Andrew Zisserman: Multiple view geometry in Computer Vision. Cambridge university press, 2003.
- ECTS information:
- Credits: 2,5
- Additional information
- Keywords: computer vision; stereo vision; structure from motion; multi-view reconstruction; convolutional neural networks
Expected participants: 150
www: https://www.studon.fau.de/crs4475489.html
- Assigned lectures
- UE: Computer Vision Exercise
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Lecturers: Prof. Dr. Bernhard Egger, Shih-Yuan Huang, Sarma Jeet Sen, Maximilian Weiherer, M. Sc., Mathias Zinnen, M. Sc., M.Sc. Darius Rückert
www: https://www.studon.fau.de/crs4475489.html
- Verwendung in folgenden UnivIS-Modulen
- Startsemester SS 2022:
- Computer Vision (CV)
- Department: Chair of Computer Science 5 (Pattern Recognition)
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