Inhalt

[ 921PECOCOVU20 ] UE Computer Vision

Versionsauswahl
(*) Unfortunately this information is not available in english.
Workload Education level Study areas Responsible person Hours per week Coordinating university
1,5 ECTS M1 - Master's programme 1. year Computer Science Oliver Bimber 1 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Computer Science 2021S
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. The associated lecture 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. This lab will provide a sufficient introduction into Matlab, Matlab toolboxes, and hands-on computer vision techniques to prepare students for their team projects.
Subject Introduction to Matlab, Introduction to Matlab's toolboxes (Image Processing and Computer Vision Toolbox), Introduction to this semester's project.
Criteria for evaluation Team Project (project presentations and results)
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 http://www.jku.at/cg/content/e48361/e174976/e48366/
Corresponding lecture (*)in collaboration with 921PECOCOVV20: VL Computer Vision (3 ECTS) equivalent to
921PECOCOVK13: KV Computer Vision (4.5 ECTS)
On-site course
Maximum number of participants 24
Assignment procedure Direct assignment