Computer vision
Topic outline
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Welcome to the Computer Vision class!
Computer Vision is the branch of Computer Science whose goal is to model the real world or to recognize objects from digital images. These images can be acquired using still and video cameras, infrared cameras, radars, or specialized sensors such as those used in the medical field.
The students will be introduced to the basic techniques of the field of Computer Vision. They will learn to apply Image Processing techniques where appropriate.
We will concentrate on the black and white and color images acquired using standard video cameras. We will introduce basic processing techniques, such as edge detection, segmentation, texture characterization, and shape recognition.Instructor
Prof. Pascal Fua
Computer Vision Laboratory (CVLAB)
BC 310
E-mail: pascal.fua@epfl.chCourse Times and Locations
Lectures: Monday 13:15 - 15:00 (https://epfl.zoom.us/j/86481362793)
Exercises: Tuesday 10:15 - 12:00 (online) - please check the course schedule and bring your own laptops for the exercise sessions.
Office Hours
If you have any questions please email one of the TAs and we can arrange a meeting.
Isinsu Katircioglu (isinsu.katircioglu@epfl.ch)
Udaranga Wickramasinghe (udaranga.wickramasinghe@epfl.ch)
Semih Günel (semih.gunel@epfl.ch)
Benoît Guillard (benoit.guillard@epfl.ch)
Michal Jan Tyszkiewicz (michal.tyszkiewicz@epfl.ch)
Davydov Andrey (andrey.davydov@epfl.ch)
Final Exam
It will be a 90min closed book exam with multiple-choice and open-ended questions. You will be allowed ONE hand-written A4 page of notes.Mock Exam
One of the exercise sessions will be devoted to a mock exam so that you know what to expect.
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22.02.2021
Course
01.03.2021
Course
02.03.2021
Exercise Session
08.03.2021
Course
15.03.2021
Course
16.03.2021
Exercise Session
22.03.2021
Course
29.03.2021
Course
30.03.2021
Exercise Session
05.04.2021
No Course (holiday)
12.04.2021
Course
19.04.2021
Course
20.04.2021
Exercise Session
26.04.2021
Course
03.05.2021
Course
04.05.2021
Mock exam 10.05.2021
Course
17.05.2021
Course
18.05.2021
Exercise Session
24.05.2021
Course
31.05.2021
Course
01.06.2021
Exercise Session
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R. Szeliki, Computer Vision: Computer Vision: Algorithms and Applications, 2021.
R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press, 2003.
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Edge definition, edge operators, Canny edge detector, and machine-learning based detectors.
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Going from edge elements to complete outlines.
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Partitioning images into separate regions of interest.
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Texture: What is it and how can it be characterized and analyzed.
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Recovering 3D shape from one single image.
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Recovering Depth from Multiple Images
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Recovering 3D shape from edges and occluding contours
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Introduction to Python for Computer Vision
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Image filtering and edge detection
