Lecturer: Oliver Bimber

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

Capturing Digital Images, Digital Image Processing, Machine Learning, Feature Extraction, Segmentation, Optical Flow, Object Detection, Camera Calibration, 3D Vision, Trends in Computer Vision

Selected Readings

1. Computer Vision: Algorithms and Applications, Richard Szeliski, Springer
2. Computer Vision – A Modern Approach, Forsyth and Ponce, Addison Wesley
3. Multiple View Geometry in Computer Vision, Hartley and Zisserman, Cambridge Press
4. Pattern Classification, Duda, Hart, and Stork, Wiley-Interscience

Criteria for Evaluation

eExam (Moodle test), physical presence in Linz, Vienna, Bregenz required

Format

Online only (Zoom), recordings, slides