Multimedia Systems

Course description


  1. Introduction to multimedia, overview of the field and challenges
  2. Manipulation of image data
  3. Video standards and manipulation of video data
  4. Text-based information retrieval
  5. Architecture of multimedia information retrieval
  6. Evaluation of multimedia systems for information retrieval
  7. Automatic image content description
  8. Segmentation of image content
  9. Segmentation of video content
  10. Interactive media and augmented reality in multimedia systems
  11. Lossless compression standards in multimedia
  12. Lossy compression standards in multimedia

Exercises and seminar:

Exercises will take a form of project-oriented exercises and seminars in properly equipped student laboratories. Students will implement various algorithms, that will be covered in lectures, and test them on different datasets using a variety of sensor systems. Exercises will support an in-depth understanding of the theory. They will also encourage independent thinking and creativity.

Course is carried out on study programme

Multimedija 1. stopnja

Objectives and competences

Multimedia systems are an indispensable part of modern information technology. In the framework of this course, the students will acquire knowledge and skills needed for use, design and development of multimedia systems. The course will also deal with the problems related to efficient representations and processing multimedia data, such as text, graphics, animations, images, and video.

In addition, the students will obtain the following competences:

  • The ability to understand and solve professional challenges in computer and information science.
  • The ability of professional communication in the native language as well as a foreign language.
  • The ability to independently perform both less demanding and complex engineering and organisational tasks in certain narrow areas and independently solve specific well-defined tasks in computer and information science.

Learning and teaching methods

Lectures, laboratory exercises in computer classroom with active participation. Individual work on excercises. Theory from the lectures made concrete with hands-on laboratory exercises. Special emphasis will be put on continuous assessment at exercises.

Intended learning outcomes

After completing this course a students will be able to:

– understand the basics of image decomposition and transformation for use in infomation and multimedia systems,

– understand the basics of text-based information retrieval systems,

– implement systems for automatic video decomposition and video querying,

– understand the basics of image and video compression used in standard codecs,

– understand the basics of augmented reality and be able to design marker-based augmented reality systems,

– know the algorithmic background of computer technologies and methodologies specific for modern multimedia applications.

Reference nosilca

LUKEŽIČ, Alan, ČEHOVIN ZAJC, Luka, VOJÍŘ, Tomáš, MATAS, Jiří, KRISTAN, Matej. Performance evaluation methodology for long-term single-object tracking. IEEE transactions on cybernetics. [Print ed.]. 2020, vol. , no. , str. 1-14, ilustr. ISSN 2168-2267. [COBISS.SI-ID 1538564803]

 ČEHOVIN ZAJC, Luka. TraX : the visual Tracking eXchange protocol and library. Neurocomputing. [Print ed.]. Oct. 2017, vol. 260, str. 5-8, ilustr. ISSN 0925-2312. [COBISS.SI-ID 1537470147],

LUKEŽIČ, Alan, ČEHOVIN ZAJC, Luka, KRISTAN, Matej. Deformable parts correlation filters for robust visual tracking. IEEE transactions on cybernetics, ISSN 2168-2267, 2017, vol. , no. , str. 1-13, [COBISS.SI-ID 1537625283],

KRISTAN, Matej, MATAS, Jiří, LEONARDIS, Aleš, VOJÍŘ, Tomáš, PFLUGFELDER, Roman, FERNÁNDEZ, Gustavo, NEBEHAY, Georg, PORIKLI, Fatih, ČEHOVIN ZAJC, Luka. A novel performance evaluation methodology for single-target trackers. IEEE transactions on pattern analysis and machine intelligence, ISSN 0162-8828. [Print ed.], Nov. 2016, vol. 38, no. 11, str. 2137-2155, [COBISS.SI-ID 1536872643]

KRISTAN, Matej, LEONARDIS, Aleš. Online discriminative kernel density estimator with Gaussian kernels. IEEE transactions on cybernetics, vol. 44, (3), 2014, str. [355-365], [COBISS.SI-ID 9907284]

ČEHOVIN, Luka, KRISTAN, Matej, LEONARDIS, Aleš. Robust visual tracking using an adaptive coupled-layer visual model. IEEE trans. pattern anal. mach. intell.. [Print ed.], 2012, str. [1-14], [COBISS.SI-ID 9431124]

Celotna bibliografija je dostopna na SICRISu:


Study materials


  • Mark S. Li Ze-Nian and Drew, Fundamentals of Multimedia, Prentice-Hall of India (2005)
  • C. D. Manning, P. Raghavan, H. Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008


  • A. Del Bimbo: Visual Information Retrieval, Morgan Kaufmann 1999, ISBN 1-55860-624-6.

Članki iz revij, kot npr. IEEE Multimedia. (dostopno na spletu)

Bodi na tekočem

Univerza v Ljubljani, Fakulteta za elektrotehniko, Tržaška cesta 25, 1000 Ljubljana

E: T:  01 4768 411