Course Syllabus for

Computer Vision

FMA271F, 7.5 credits

Valid from: Autumn 2013
Decided by: FN1/Anders Gustafsson
Date of establishment: 2014-01-31

General Information

Division: Mathematics
Course type: Course given jointly for second and third cycle
The course is also given at second-cycle level with course code: FMA270
Teaching language: English


The aim of the course is to give necessary knowledge for further research within computer vision and in order to use computer vision methods within other research areas, e.g. robotics, vision systems, non-invasive measurements and augmented reality.


Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must

Course Contents

Projective geometry. Geometric transformations. Modelling cameras. Stereo vision. Photogrammetry. Recognition. 3D-modelling. Geometry of surfaces and their silhouettes. Visualisation.

Course Literature

Szeliski, R.: Computer Vision: Algorithms and Applications. Springer, 2010. ISBN 9781848829343.
It is possible to pass the course using handouts.

Instruction Details

Types of instruction: Lectures, laboratory exercises, exercises

Examination Details

Examination formats: Written exam, oral exam, written assignments
Grading scale: Failed, pass

Admission Details

Course Occasion Information

Contact and Other Information

Course coordinators:

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