Computer vision CS-442 / 6 credits
Teacher: Fua Pascal
Language: English
Summary
Computer Vision aims at modeling the world from digital images acquired using video or infrared cameras, and other imaging sensors. We will focus on images acquired using digital cameras. We will introduce basic processing techniques and discuss their field of applicability.
Content
Introduction History of Computer Vision Human vs Machine Vision Image formation Extracting 2D Features Contours Texture Regions 3D Shape Recovery From one single image From multiple images
Learning Outcomes
By the end of the course, the student must be able to:
Choose relevant algorithms in specific situations Perform simple image-understanding tasks Teaching methods
Ex cathedra lectures and programming exercises using Python.
Assessment methods
With continuous control
Resources
BIBLIOGRAPHY
R. Szeliski, Computer Vision: Computer Vision: Algorithms and Applications, 2010. A. Zisserman and R. Hartley, Multiple View Geometry in Computer Vision, Cambridge University Press, 2003.
RESSOURCES EN BIBLIOTHÈQUE
Computer Vision: Algorithms and Applications / Szeliski Multiple View Geometry in Computer Vision / Zisserman MOODLE LINK