[ 921PECOCOVK13 ] KV Computer Vision

Es ist eine neuere Version 2019W dieser LV im Curriculum Master's programme Computer Science 2019W vorhanden.
(*) Unfortunately this information is not available in english.
Workload Education level Study areas Responsible person Hours per week Coordinating university
4,5 ECTS M1 - Master's programme 1. year Computer Science Oliver Bimber 3 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Computer Science 2016W
Objectives 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.
Subject 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 image processing toolbox, introduction into lightfield processing.
Criteria for evaluation Written exam (oral exam in exceptional cases), practical lab assignment
Methods Slide presentation with case studies
Language English
Study material 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

Changing subject? No
Further information
Corresponding lecture (*)938PECKCOVK12: KV Computer Vision (4,5 ECTS) or INMPPKVMRSY: KV Mixed Reality Systems (4,5 ECTS)
On-site course
Maximum number of participants -
Assignment procedure Direct assignment