Inhalt

[ 921PECOCOVU20 ] UE (*)Computer Vision

Versionsauswahl
(*) 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 2024W
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 lecture will give insights into the basics of Computer Vision and links to corresponding machine learning approaches. It requires basic knowledge of machine learning principles.
Lehrinhalte (*)Introduction to Matlab, Introduction to Matlab's toolboxes (Image Processing and Computer Vision Toolbox), Introduction to this semester's project.
Beurteilungskriterien (*)eExam (Moodle test), physical presence in Linz, Vienna, Bregenz required
Lehrmethoden (*)Online only (Zoom), recordings, slides.
Abhaltungssprache Englisch
Literatur (*)
  1. Computer Vision: Algorithms and Applications, Richard Szeliski, Springer, ISBN: 1848829345, 2010
  2. Computer Vision – A Modern Approach, Forsyth and Ponce, 2nd edition, Addison Wesley, ISBN-10: 013608592X, 2011
  3. Multiple View Geometry in Computer Vision, Hartley and Zisserman, 2nd edition, Cambridge Press, ISBN: 0521540518, 2003
  4. Pattern Classification, Duda, Hart, and Stork, 2nd edition, Wiley-Interscience, ISBN: 978-0-471-05669-0, 2000
Lehrinhalte wechselnd? Nein
Äquivalenzen (*)in collaboration with 921PECOCOVV20: VL Computer Vision (3 ECTS) equivalent to
921PECOCOVK13: KV Computer Vision (4.5 ECTS)
Präsenzlehrveranstaltung
Teilungsziffer 24
Zuteilungsverfahren Direktzuteilung