Grading scheme: 50 points for assignments, 50 points for written (closed book) exam. [50-65 -> 3; 66-85 -> 2; 86-100 -> 1]
The number of images and videos around us, especially on the internet, is ever
growing. The demand on processing the available visual information is also
increasing and new applications are emerging.
We will learn essential computer vision algorithms for the above applications.
Prerequisites: linear algebra and probability theory at undergraduate level,
some knowledge of image processing is advantageous but it is not required
Subject grading: 50 points for assignments and tests, 50 points for written
(closed book) exam. [50-65 -> 3; 66-85 -> 2; 86-100 -> 1]. Written
examination takes 90 minutes. Further questions will be asked after the written
exam is evaluated.
You may be asked a question from basics of linear algebra
or probability theory. Failing to answer such a question implies failing the exam. The list
of the question will be posted here.
Vector norm, dot product, orhogonality.
Linearly (in)dependent vectors.
Systems of linear equations.
Least squares formulation and solution.
Probability, binomial coefficients.
19th January, 12:45
Lecture schedule with links to
slides. Please note the Last update column which shows the last update
of the lecture slides.
There is no single book which would cover the topic entirely. The
lecture slides (notes) are usually accompanied with references to
recommended reading. Generally, we will make use of the following books: