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.
Examination
The course uses grades A-F. Work during the semester 50%, written part of the exam 40%, oral part of the exam 10% (both parts of the exam are online for EuroTeQ students). For details, see the course website: https://cw.fel.cvut.cz/wiki/courses/mpv/start
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, programming exercises, homeworks
Additional information
- Coordinating facultyCzech Technical University in Prague
- Contact a coordinator
- LevelMaster
- Contact hours per week4
- InstructorsIng. Yermakov Andrii, Ing. Šerých Jonáš Ph.D., Ing. Šuma Pavel, doc. Tolias Georgios Ph.D., prof. Ing. Matas Jiří Ph.D., Ing. Čech Jan Ph.D., Mgr. Mishkin Dmytro Ph.D., Ing. Neumann Lukáš Ph.D.
- Mode of deliveryHybrid