Course

CS-442: Computer vision

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.

Lectures

Instructor

Pascal Fua

Pascal Fua received an engineering degree from Ecole Polytechnique, Paris, in 1984 and the Ph.D. degree in Computer Science from the University of Orsay in 1989. He then worked at SRI International and INRIA Sophia-Antipolis as a Computer Scientist. He joined EPFL in 1996 where he is now a Professor in the School of Computer and Communication Science and heads the Computer Vision Laboratory. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and Augmented Reality. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and machine learning. He has (co)authored over 300 publications in refereed journals and conferences. He is an IEEE Fellow and has been an Associate Editor of IEEE journal Transactions for Pattern Analysis and Machine Intelligence. He often serves as program committee member, area chair, and program chair of major vision conferences and has cofounded three spinoff companies (Pix4D, PlayfulVision, and NeuralConcept).

Official source

https://edu.epfl.ch/coursebook/en/computer-vision-CS-442

Moodle Page

http://go.epfl.ch/CS-442

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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.

Lectures

Instructor

Pascal Fua

Official source

https://edu.epfl.ch/coursebook/en/computer-vision-CS-442

Moodle Page

http://go.epfl.ch/CS-442

Lectures in this course (31)

CS-442 Summer 2024

Image Formation: Understanding 2D Projections from 3D Scenes

Explains the principles of image formation, covering light projection, digitization, and the pinhole camera model.

Deep Learning: Edge Detection and Neural Networks

Discusses edge detection techniques and the evolution of deep learning in neural networks.

CS-442 Summer 2024

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