Course details

Computational Photography

VYF Acad. year 2024/2025 Summer semester 5 credits

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.

Guarantor

Čadík Martin, doc. Ing., Ph.D. (DCGM)

Language of instruction

Czech

Completion

Classified Credit (written)

Time span

  • 26 hrs lectures
  • 26 hrs projects

Assessment points

  • 40 pts mid-term test
  • 60 pts projects

Department

Department of Computer Graphics and Multimedia (UPGM)

Lecturer

Čadík Martin, doc. Ing., Ph.D. (DCGM)

Instructor

Čadík Martin, doc. Ing., Ph.D. (DCGM)

Learning objectives

Methods of computational photography stand at the border of image processing, computer vision, computer graphics, physics, visual perception and other fields. The course offers the student a comprehensive view of this intersection, while a number of principles are demonstrated practically directly during the lectures (classical photography, HDR acquisition, tone mapping, image registration, spherical panoramic images, etc.). Students have the opportunity to participate in photo challenges and receive feedback from peers and lecturers. Previous knowledge of taught subjects on computer vision, graphics, or image processing is an advantage, but not required.

Fundamental literature

  • Radke, R.: Computer Vision for Visual Effects. Cambridge university press.  2013.
  • Szeliski, R.: Computer Vision: Algorithms and Applications, Springer. 2010.

  • Shirley, P., Marschner, S.: Fundamentals of Computer Graphics. CRC Press. 2009.

Syllabus of lectures

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

Progress assessment

  1. Project proposals
  2. Project assignments
  3. --
  4. --
  5. Consultations after the lecture - literature
  6. --
  7. Consultations after the lecture - implementation
  8. --
  9. Consultations after the lecture - testing
  10. --
  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.

Schedule

DayTypeWeeksRoomStartEndCapacityLect.grpGroupsInfo
Mon lecture lectures L314 11:0012:5030 1MIT 2MIT xx Čadík

Course inclusion in study plans

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