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Computer Vision Methods

BE4M33MPV
Computer Science and ICT, Data, AI

About this course

The course covers selected computer vision problems: search for correspondences between images via interest point detection, description and matching, image stitching, detection, recognition and segmentation of objects in images and videos, image retrieval from large databases and tracking of objects in video sequences.

This course is also part of the inter-university programme prg.ai Minor. It pools the best of AI education in Prague to provide students with a deeper and broader insight into the field of artificial intelligence. More information is available at https://prg.ai/minor.

Learning outcomes

The methods for image registration, retrieval and for object detection and tracking are explained. In the labs, the students implement selected methods and test performance on real-world problems.

Course requirements

Knowledge of calculus and linear algebra.

Resources

  • 1.M. Sonka, V. Hlavac, R. Boyle. Image Processing, Analysis and Machine Vision. Thomson 2007
  • 2.D. A. Forsyth, J. Ponce. Computer Vision: A Modern Approach. Prentice Hall 2003

Activities

Lecures and lab-work

Additional information

  • Credits
    ECTS 6
  • Contact hours per week
    4
  • Instructors
    Ing. Šuma Pavel, doc. Tolias Georgios Ph.D., prof. Ing. Matas Jiří Ph.D., Ing. Čech Jan Ph.D., Mgr. Drbohlav Ondřej Ph.D., Mgr. Mishkin Dmytro Ph.D., Ing. Neumann Lukáš Ph.D.
  • Mode of instruction
    Hybrid
If anything remains unclear, please check the FAQ of CTU (Czech Republic).

Offering(s)

  • Start date

    17 February 2025

    • Ends
      21 September 2025
    • Term *
      Summer 2024/2025
    • Instruction language
      English
    • Register between
      24 Oct - 24 Nov 2024
    Enrolment open
    Apply now
These offerings are valid for students of TUM (Germany)