Weekly outline

  • About

    Disclaimer: This course is officially held in English. All the materials, lectures are in English. But you can also communicate with lecturer in Slovenian if you feel more comfortable.

    Lectures start on Wednesday, 6th of October 2021 at 12:15 in PR01. Laboratory exercises will start one week after the lectures.

    To pass the course you have to complete theoretical (exam) and practical part. The practical part is either regular exercises or a project that spans the entire semester.

    Laboratory exercises include six separate exercises, for each you have about two weeks' time. The result of each exercise is a source code that is submitted on Učilnica and presented in the classroom to the assistant. Defending each exercise is only possible during the designated deadline week for that exercise (see introductory slides for laboratory exercises). To pass the practical part of the course you have to successfully present all six exercises. This is a requirement to attend the exam. In case you cannot present your work during the designated week you can do it one week later with a penalty factor of 0.75. In rare cases where you cannot present even then (long illness, vacation, etc.) you can present the work for a single exercise at the end of the semester (the Joker week). It is also important that you present your work only during the laboratory cycle that you have been assigned to. Laboratory exercises are done in Python (IPython and Jupyter).

    Practical project involves in-depth study of a single topic that ends with a prototype of a practical application or a service that is presented at the end of the semester during the lectures.

    Course literature:

    • Lecture slides
    • Lecture notes
    • Ze-Nian Li and Mark S. Drew, "Fundamentals of Multimedia", Pearson. 2004.
    • C. D. Manning, P. Raghavan, H. Schütze, "Introduction to Information Retrieval", Cambridge University Press. 2008. accessible here: http://nlp.stanford.edu/IR-book/
    • Richard Szeliski,"Computer Vision: Algorithms and Applications", accessible here: http://szeliski.org/Book/.
    • Bimbo, del, A. "Visual Information Retrieval", Morgan Kauffman, 1999
  • 5 October - 11 October

    Lectures: Introduction, Machine learning in Multimedia, Image Formation
    Exercises: no laboratory exercises first week

  • 12 October - 18 October

    Lectures: Image processing
    Exercises: Introductory information, tutorial on Python and Numpy, First exercise

  • 19 October - 25 October

    Lectures: Image processing
    Exercises: Consultations

  • 26 October - 1 November

    Lectures: Video acquisition, video processing
    Exercises: Second exercise is public, first exercise presentation