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Root number
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102470 |
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Semester
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HS2023 |
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Type of course
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Lecture |
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Allocation to subject
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Computer Science |
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Type of exam
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Written exam |
| Title |
Computer Vision |
| Description |
This course covers fundamental topics in computer vision. The course will provide an introduction to image formation, image processing, feature detection, segmentation, multiple view geometry and 3D reconstruction, motion, object recognition and classification.
Material (all covered in the slides)
Introduction & projection models (also see book: Forsyth & Ponce Ch 1 & 2)
Camera models, image filtering (also see book: Forsyth & Ponce Ch 1 & 2, Ch. 7 & 8)
Edges, deblurring, denoising, numerical methods (also see book: Forsyth & Ponce Ch. 7 & 8)
Photometric stereo & shading (book: Forsyth & Ponce Ch 4 & 5)
Tracking, optical flow (book: Forsyth & Ponce Ch 17)
Interest points detection (book: Grauman & Leibe)
Registration and fitting (book: Forsyth & Ponce Ch 15)
Epipolar geometry & stereo (book: Forsyth & Ponce Ch 10 & 11)
Multiview stereo and structure from motion (book: Forsyth & Ponce Ch 12 & 13)
Recognition (book: Grauman & Leibe)
Bayesian methods in imaging (slides only)
Clustering and segmentation (book: Forsyth & Ponce Ch 14, 15 & 16)
Revision (source:Handouts)
The following books are recommended as additional reading:
• Computer Vision : A Modern Approach, David A. Forsyth and Jean Ponce.
• Algorithms and Applications, Rick Szeliski.
An electronic copy is also available free online (http://szeliski.org/Book/).
• Visual Object Recognition, Kristen Grauman and Bastian Leibe.
This book is also available online for free.
There will be 2 assignments and the deadlines will be specified at the beginning of the course.
For admission to the examination one must pass every assignment. The assignments will also
contribute to 30% of the final mark. The description of each assignment will be made available
in Ilias. Notice that assignments will require use of Python.
All the homework assignments are also intended for exam preparation. |
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ILIAS-Link (Learning resource for course)
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Link to another web site
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| Lecturers |
Prof. Dr.
Paolo Favaro, Institute of Computer Science ✉
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ECTS
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5 |
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Recognition as optional course possible
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No |
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Grading
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1 to 6 |
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| Dates |
Monday 14:15-17:00 Weekly
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| Rooms |
Hörraum 101, Hauptgebäude H4
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| Students please consult the detailed view for complete information on dates, rooms and planned podcasts. |
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Öffentlicher Bereich
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