Lecturer: Mohammed Abbass

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 lab is complementary to the Computer Vision lecture. It requires knowledge in python programming and basics of machine learning.

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

Assignments

Format

Onboarding labs and open labs, mainly online only (Zoom), selected appointments hybrid, recordings, slides.