Faculty of Information Technology, BUT

Course details

Computer Vision

POVa Acad. year 2017/2018 Winter semester 5 credits

Principles and methods of computer vision, methods and principles of image acquiring, preprocessing methods (statistical processing), filtering, pattern recognition, integral transformations - Fourier transform, image morphology, classification problems, automatic classification, D methods of computer vision, open problems of computer vision.

Guarantor

Language of instruction

English

Completion

Examination (written)

Time span

26 hrs lectures, 26 hrs projects

Assessment points

51 exam, 9 half-term test, 40 projects

Department

Lecturer

Instructor

Bartl Vojtěch, Ing. (DCGM FIT BUT)
Behúň Kamil, Ing. (DCGM FIT BUT)
Hradiš Michal, Ing., Ph.D. (DCGM FIT BUT)
Juránek Roman, Ing., Ph.D. (DCGM FIT BUT)
Sochor Jakub, Ing. (DCGM FIT BUT)
Špaňhel Jakub, Ing. (DCGM FIT BUT)

Subject specific learning outcomes and competences

The students will get acquainted with the principles and methods of computer vision. They will learn in more detail selected methods and algorithms of vision and image acquiring. They will also get acquainted with the possibilities of the scanned data processing. Finally, they will learn how to apply the gathered knowledge practically.

Generic learning outcomes and competences

The students will improve their teamwork skills, mathematics, and exploitation of the "C" language.

Learning objectives

To get acquainted with the principles and methods of computer vision. To learn in more detail selected methods and algorithms of vision and image acquiring. To get acquainted with the possibilities of the scanned data processing. To learn how to apply the gathered knowledge practically.

Study literature

  • Russ, J.C.: The IMAGE PROCESSING Handbook, CRC Press, 1995, ISBN 0-8493-2532-3
  • Bass, M.: Handbook of Optics, McGraw-Hill, New York, USA, 1995, ISBN 0-07-047740-X

Fundamental literature

  • Horn, B.K.P.: Robot Vision, McGraw-Hill, 1988, ISBN 0-07-030349-5
  • Hlaváč, V., Šonka, M.: Počítačové vidění, Grada, 1993, ISBN 80-85424-67-3 
  • Russ, J.C.: The IMAGE PROCESSING Handbook, CRC Press, 1995, ISBN 0-8493-2532-3
  • Bass, M.: Handbook of Optics, McGraw-Hill, New York, USA, 1995, ISBN 0-07-047740-X

Syllabus of lectures

  1. Úvod, základy, motivace a aplikace/Introduction, motivation and applications (Zemčík 18.9. slajdyslajdyhighlights)
  2. 28.9. přednáška není/no lecture :-(
  3. Základní principy klasifikace s učitelem - AdaBoost/Basic principles of machine learning with teacher - AdaBoost  (Zemčík 5.10. slajdy-czslajdy-en)
  4. Shlukování, statistické metody/Clustering, statistical methods (Španěl 12.10. slajdy)
  5. Segmentace, analýza barev, analýza histogramu/Segmentation, colour analysis, histogram analysis (Španěl 19.10. slajdy1slajdy2slajdy3)
  6. Analýza a extrakce příznaků z textur/Analysis and Feature Extraction from Images (Čadík 26.10. slajdy)
  7. Hough transform, RHT, RANSAC, zpracování časových sekvencí/Time Sequence Processing (Hradiš, 2.11. slajdy1,  slajdy2slajdy2-en)
  8. Segmentace,  analýza barev/Segmentation, Colour Analysis, ... finishing (Španěl), Object Detection - Trees (Juránek, 9.11. slajdy1slajdy2)
  9. Test, Invariantní Oblasi Obrazu/Invariant Image Regions (Beran, 16.11. slajdy)
  10. Konvoluční neuronové sítě a Tagování obrazu/Convolutional Neural Networks and Automatic Image Tagging (Hradiš, 23.11. slajdy)
  11. 3D Vision/3D Vidění (30.11. ??? slajdy)
  12. Registrace obrazu (Čadík, 7.12., slajdy)
  13. Akcelerace zpracování obrazu, závěr (Zemčík???, 14.12.)
  14.   

Syllabus - others, projects and individual work of students

  1. Homeworks (5 runs) at the beginning of semester
  2. Individually assigned project for the whole duration of the course.

Progress assessment

Homeworks, Mid-term test, individual project.

Course inclusion in study plans

  • Programme IT-MSC-2, field MBI, MBS, MMI, MMM, MSK, any year of study, Elective
  • Programme IT-MSC-2, field MGM, MPV, any year of study, Compulsory-Elective group G
  • Programme IT-MSC-2, field MIN, any year of study, Compulsory-Elective group I
  • Programme IT-MSC-2, field MIS, 2nd year of study, Elective
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