Inhalt
[ 921PECOCOVU20 ] UE Computer Vision
|
|
|
|
|
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 |
- Computer Vision: Algorithms and Applications, Richard Szeliski, Springer, ISBN: 1848829345, 2010
- Computer Vision – A Modern Approach, Forsyth and Ponce, 2nd edition, Addison Wesley, ISBN-10: 013608592X, 2011
- Multiple View Geometry in Computer Vision, Hartley and Zisserman, 2nd edition, Cambridge Press, ISBN: 0521540518, 2003
- 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 |
|
|
|