Course Computer Vision 1
Master Artificial Intelligence
This is the information of Fall 2024
This year the course will be given by Arnoud Visser and Martin Oswald as lecturers.
Description
The description is available in the course catalogue with code COV6Y. The course is a free choice in the Master Artificial Intelligence Curriculum.
Contents
This course gives an introduction in the fundamentals of perception algorithms.This course is based on the book Computer Vision - Algorithms and Applications.
The assignments are all Python based.
Schedule
The official schedule should be found at mytimetable or datanose.
Personally, I will give the first part of the lectures:
Week 36: Lecture - Camera geometry
Week 36: Lecture - Image formation and Color
Week 37: Lecture - Reflection model
Week 37: Lecture - image filtering
Week 38: Lecture - Edges and corners
Week 38: Lecture - Optical flow
Literature
Richard Szeliski, Computer Vision - Algorithms and Applications, Springer Texts in Computer Science, 2nd edition, 2022
Antonio Torralba, Phillip Isola, William T. Freeman, Foundations of Computer Vision, MIT Press, 2024.
Embedding in AI curriculum
This course is supported by the following chapters of 'Artificial Intelligence - A Modern Approach' 4th edition, by Stuart Russell and Peter Norvig:- Chapter 25: Computer Vision
Links
- Linda Shapiro, Computer Vision, University of Washingthon, Spring 2024.
- Phillip Isola, William T. Freeman, Advances in Computer Vision, MIT CSAIL, Spring 2024.
Software toolkits
Last updated August 22, 2024
This web-page and the list of participants to this course is maintained by