en:courses:3020

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Number: 3020 Title: Computer Vision English Title: Computer Vision Level: MicroMaster Field: Artificial Intelligence Units: 3 Type: Theoretical Category: Fundamental Priority: 20 Prerequisite: General Objective Co-requisite: – Image: vision.png ID: 3020 Instructor: Education Term: Summer 2025 Schedule: Tuesday 14:00-17:00

General Objective

"Computer Vision" refers to a set of methods and algorithms that enable computers to understand the content of images and videos. In this course, students will learn about data acquisition and processing methods, scene understanding, object classification, and 3D scene reconstruction. They will acquire fundamental theoretical knowledge and become familiar with modern applications in the field.

Topics

Course introduction, basic definitions, and applications
Review of signal and image processing
3D geometry
Cameras and projection
3D reconstruction
Multi-view reconstruction
Keypoint extraction
Keypoint matching
Robust model fitting
Data grouping (clustering, segmentation, and classification)
Deep learning in computer vision

Assessment

Final Exam: 14 points
Assignments and Project: 6 points

References

KTH Lecture Notes on Geometric Computing, Stefan Carlsson, http://www.nada.kth.se/~stefanc/gc_lec_notes.pdf
Computer Vision: Algorithms and Applications, Richard Szeliski, Springer; 1st Edition (Oct. 1, 2010), ISBN-10: 1848829345, ISBN-13: 978-1848829343.
An Invitation to 3-D Vision, Yi Ma, Stefano Soatto, Jana Kosecka, & Shankar Sastry, Springer (November 14, 2003), ISBN-10: 0387008934, ISBN-13: 978-0387008936.
Computer Vision – A Modern Approach, David A. Forsyth & Jean Ponce, Prentice Hall; US ed Edition (August 24, 2002), ISBN-10: 0130851981, ISBN-13: 978-0130851987.