Course detail

Computational Photography

FIT-VYFAcad. year: 2020/2021

Current digital cameras almost completely surpass traditional photography. They do not only capture light, they in fact compute pictures. That said, there is practically no image that would not be computationally processed to some extent today. Visual computing is ubiquitous. Unfortunately, images taken by amateur photographers often lack the qualities of professional photos and some image editing is necessary. Computational photography (CP) develops methods to enhance or extend the capabilities of the current digital imaging chain.

Language of instruction

Czech

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

doc. Ing. Martin Čadík, Ph.D.

Department

Department of Computer Graphics and Multimedia (UPGM)

Learning outcomes of the course unit

Not applicable.

Prerequisites

Not applicable.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

  1. Project proposals
  2. Project assignments
  5. Consultations after the lecture - literature
  7. Consultations after the lecture - implementation
  9. Consultations after the lecture - testing
  11. WRITTEN EXAM
  12. Finished implementations
  13. Presentations of assignments, final reports

Exam prerequisites:
It is obligatory to be present at the written exam, submit the project including textual report and oral presentation. At least 50 points must be obtained, while the minimal score from the test is 16 points, the minimal score from the project is 24 points. During the term, one can get bonus points in practical photography challenges.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

The aim is to introduce computational photography methods (http://cphoto.fit.vutbr.cz/) and to get acquainted with the principles of mathematics and computer science in the field.

Specification of controlled education, way of implementation and compensation for absences

Not applicable.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Radke, R.: Computer Vision for Visual Effects. Cambridge university press.  2013.

Recommended reading

Radke, R.: Computer Vision for Visual Effects. Cambridge university press.  2013.
Shirley, P., Marschner, S.: Fundamentals of Computer Graphics. CRC Press. 2009.
Szeliski, R.: Computer Vision: Algorithms and Applications, Springer. 2010.

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MGM , 0 year of study, summer semester, elective
    branch MBI , 0 year of study, summer semester, elective
    branch MBS , 0 year of study, summer semester, elective
    branch MIN , 0 year of study, summer semester, elective
    branch MIS , 0 year of study, summer semester, elective
    branch MMI , 0 year of study, summer semester, elective
    branch MMM , 0 year of study, summer semester, elective
    branch MPV , 0 year of study, summer semester, elective
    branch MSK , 0 year of study, summer semester, elective

  • Programme MITAI Master's

    specialization NISY , 0 year of study, summer semester, elective
    specialization NADE , 0 year of study, summer semester, elective
    specialization NBIO , 0 year of study, summer semester, elective
    specialization NCPS , 0 year of study, summer semester, elective
    specialization NEMB , 0 year of study, summer semester, elective
    specialization NHPC , 0 year of study, summer semester, elective
    specialization NGRI , 0 year of study, summer semester, elective
    specialization NIDE , 0 year of study, summer semester, elective
    specialization NISD , 0 year of study, summer semester, elective
    specialization NMAL , 0 year of study, summer semester, elective
    specialization NMAT , 0 year of study, summer semester, elective
    specialization NNET , 0 year of study, summer semester, elective
    specialization NSEC , 0 year of study, summer semester, elective
    specialization NSEN , 0 year of study, summer semester, elective
    specialization NSPE , 0 year of study, summer semester, elective
    specialization NVER , 0 year of study, summer semester, elective
    specialization NVIZ , 0 year of study, summer semester, elective

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Ing. Martin Čadík, Ph.D.

Syllabus

  1. introduction to CP, light and color (slajdy, projekty)
  2. photography, optics, physics, sensors, noise (slajdy)
  3. visual perception, natural image statistics (slajdy)
  4. image blending (slajdy)
  5. Color, color spaces, color transfer, color-to-grayscale image conversions (slajdy)
  6. High dynamic range (HDR) imaging - acquisition, storage and display (slajdy, HDR)
  7. High dynamic range (HDR) imaging - tone mapping, inverse tone mapping (slajdy)
  8. Image registration for computational photography (slajdy)
  9. Computational illumination, dual photography, illumination changes (slajdy)
  10. Image and video quality metrics (slajdy)
  11. Omnidirectional camera, lightfields, synthetic aperture
  12. Non-photorealistic camera, computational aesthetics
  13. Computational video, GraphCuts, editing software, guests

Project

26 hod., compulsory

Teacher / Lecturer

doc. Ing. Martin Čadík, Ph.D.