Elena Sikudova


Practical course in computer vision - materials

Class evaluation:

2 small assignments during the semester (10 points each, individual work)
1 big assignment at the end of the semester (20 points, teamwork 2-3 students)
You will pass, if you get more than 20 points

Lecture 1:


Lecture 2:

slides, matlab code, mosaic image

Lecture 3:

slides, lecture matlab code, einstein image, eye image

HW1, part 1:

homework project 1 (part 1), computeHOG code
hand in ONLY the code
next week before class by mail
sign the mail (mail without your name is not counted as a solution)
HW solution code for negative samples

Lecture 4:

slides, lecture matlab code

HW1, part 2:

homework project 1 (part 2)
hand in the PDF
next week before class by mail
sign the mail

Lecture 5:

slides, images, macbeth palette, lecture matlab code

Lecture 6:

slides, images, lecture matlab code

Lecture 7:

slides, data, lecture matlab code


task description
due date: before class in two weeks (5., 6.12.)
follow the instructions

Lecture 8:

slides, image, lecture matlab code

Lecture 9:

slides, data, lecture matlab code

Lecture 10:

slides, data, lecture matlab code

Lecture 11:

slides, data

Lecture 12:



task description
due date: in 4 weeks the latest (6., 7.2.)
follow the instructions, look in the slides as well

kniha Počítačové videnie

Book cover

Errata k tlačenej knihe

My current projects

A Gamut-Mapping Framework for Color-Accurate Reproduction of HDR Images
Elena Sikudova, Tania Pouli, Alessandro Artusi, Ahmet Oguz Akyuz, Francesco Banterle, Zeynep Miray Mazlumoglu, Erik Reinhard

IEEE Computer Graphics and Applications, vol.36, no. 4, pp. 78-90, July-Aug. 2016, doi:10.1109/MCG.2015.116

IEEE Computer Graphics and Applications


Supplemental materials

Copyright (C) 2017 E.Sikudova