Introduction to Computer Vision

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Cybernetics

Synopsis:

This is an introductory course of computer vision for PhD student. Previous knowledge about the subject is not required. I will teach in Czech provided that all people in the audience understand Czech. Otherwise I teach in English.

See http://cmp.felk.cvut.cz/cmp/courses/P33ZVD/P33ZVDzima2007plan.htm

Requirements:

Without explicit prerequisites.

Syllabus of lectures:

01. What is computer vision? Digital image. Image formation, acquisition.

02. Image analysis as analysis of a 2D signal. Fourier transform rehearsal. Image preprocessing in frequency domain.

03. Image preprocessing in image domain. Edge detection. Scale space.

04. Basics of pattern recognition.

05. Image segmentation.

06. Description of objects in images. Detection of distinguished primitives in images.

07. 3D vision geometry. A single camera and more cameras.

08. Correspondence problem. Reconstruction of 3D scenes.

09. Mathematical morphology.

10. Color. Texture.

11. Image and video compression.

12. Motion analysis. Motion detection. Optical flow.

13. Tracking in videosequences.

14. Practical applications of computer vision.

Syllabus of tutorials:

See

http://cmp.felk.cvut.cz/cmp/courses/P33ZVD/P33ZVDzima2007plan.htm

Study Objective:

Study materials:

Šonka M., Hlaváč V., Boyle R.: Image processing, analysis and machine vision, 3rd edition, Thomson Engineering, Toronto, Canada, 2007.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: