Computer Vision Methods

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.

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.

Knowledge of calculus and linear algebra.

• 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

Lecures and lab-work