Inhalt

[ 921PECOCOVU20 ] UE Computer Vision

Versionsauswahl
Es ist eine neuere Version 2024W dieser LV im Curriculum Masterstudium Wirtschaftsinformatik 2024W vorhanden.
(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
1,5 ECTS M1 - Master 1. Jahr Informatik Oliver Bimber 1 SSt Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Masterstudium Computer Science 2020W
Ziele While Computer Graphics focusses on image synthesis, Computer Vision is all about image analysis and image understanding. It finds many 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. This course will give first insights into the basics of Computer Vision. At the end of the semester, participants of this class will be able to apply and implement computer vision methods independently. A basic understanding of programming concepts is required. Detailed knowledge in a programming language, however, is not necessary. A sufficient introduction into Matlab is part of the hands-on component of this class. The class is structured into interleaved lectures, labs and seminars.
Lehrinhalte Spatial and frequency domain processing, gradient domain processing, segmentation and object recognition, basics of cameras, geometric camera calibration, the geometry of multiple views, stereoscopic depth estimation, range scanning and data processing, structure from motion, computational photography, introduction into Matlab and Matab's toolboxes.
Beurteilungskriterien Schriftliche Prüfung (mündliche Prüfung in Ausnahmefällen), pratkische Übungsaufgabe
Lehrmethoden Slide presentation with case studies
Abhaltungssprache Englisch
Literatur 1) Computer Vision – A Modern Approach, Forsyth and Ponce, 2nd edition, Addison Wesley, ISBN-10: 013608592X, 2011

2) Multiple View Geometry in Computer Vision, Hartley and Zisserman, 2nd edition, Cambridge Press, ISBN: 0521540518, 2003

3) Computer Vision: Algorithms and Applications, Richard Szeliski, Springer, ISBN: 1848829345, 2010

4) Image Processing: The Fundamentals, Maria Petrou and Costas Petrou, Wiley, 2nd edition, ISBN-10: 047074586X, 2010

5) Learning OpenCV: Computer Vision with the OpenCV Library, Gary Bradski, Adrian Kaehler, Mike Loukides, Robert Romano, O'Reilly Media, ISBN: 9780596516130, 2008

6) Handbook of Mathematical Models in Computer Vision, Nikos Paragios and Yunmei Chen, Springer, ISBN-10: 0387263713, 2005

7) Machine Vision. Theory , Algorithms, Practicalities: Theory, Algorithms, Practicalities: Theory , Algorithms, Practicalities, E. R. Davies, Academic Press, 3rd edition, ISBN: 978012206093, 2005

8) Computational Vision: Information Processing in Perception and Visual Behavior, Hanspeter A. Mallot, MIT Press, ISBN: 9780262133814, 2000

9) Three-Dimensional Computer Vision – A Geometric Approach, Olivier Faugeras, MIT, Press, ISBN: 0262061589, 1993

Lehrinhalte wechselnd? Nein
Sonstige Informationen http://www.jku.at/cg/content/e48361/e174976/e48366/
Äquivalenzen in collaboration with 921PECOCOVV20: VL Computer Vision (3 ECTS) equivalent to
921PECOCOVK13: KV Computer Vision (4.5 ECTS)
Präsenzlehrveranstaltung
Teilungsziffer 24
Zuteilungsverfahren Direktzuteilung