Inhalt

[ 921PECOCOVU20 ] UE Computer Vision

Versionsauswahl
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 2024W
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 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.
Subject Introduction to Matlab, Introduction to Matlab's toolboxes (Image Processing and Computer Vision Toolbox), Introduction to this semester's project.
Criteria for evaluation eExam (Moodle test), physical presence in Linz, Vienna, Bregenz required
Methods Online only (Zoom), recordings, slides.
Language English
Study material
  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
Changing subject? No
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