Title:

Computational Photography

Code:VYF
Ac.Year:2017/2018
Term:Summer
Curriculums:
ProgrammeFieldYearDuty
IT-MSC-2MBI-Elective
IT-MSC-2MBS-Elective
IT-MSC-2MGM-Elective
IT-MSC-2MIN-Elective
IT-MSC-2MIS-Elective
IT-MSC-2MMI-Elective
IT-MSC-2MMM-Elective
IT-MSC-2MPV-Elective
IT-MSC-2MSK-Elective
Language of Instruction:Czech
Credits:5
Completion:classified credit
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:2600026
 ExaminationTestsExercisesLaboratoriesOther
Points:0400060
Guarantor:Čadík Martin, doc. Ing., Ph.D., DCGM
Lecturer:Čadík Martin, doc. Ing., Ph.D., DCGM
Faculty:Faculty of Information Technology BUT
Department:Department of Computer Graphics and Multimedia FIT BUT
Schedule:
DayLessonWeekRoomStartEndLect.Gr.St.G.EndG.
Wedpříprava VYFlecturesE10411:0011:50
WedlecturelecturesE10412:0013:501MITxxxx
WedlecturelecturesE10412:0013:502MITxxxx
 
Learning objectives:
  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.
Description:
  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.
Syllabus of lectures:
 
  1. introduction to CP, light and color (slides, projects, final report template)
  2. photography, optics, physics, sensors, noise (slides)
  3. visual perception, natural image statistics (slides)
  4. image blending (slides)
  5. Color, color spaces, color transfer, color-to-grayscale image conversions (slides)
  6. High dynamic range (HDR) imaging - acquisition, storage and display (slides, HDR)
  7. High dynamic range (HDR) imaging - tone mapping, inverse tone mapping (slides)
  8. Image registration for computational photography (slajdy, pano Canon, pano Ricoh)
  9. Computational illumination, dual photography, illumination changes (slajdy)
  10. Image and video quality metrics (slides)
  11. Omnidirectional camera, lightfields, synthetic aperture
  12. Non-photorealistic camera, computational aesthetics
  13. Computational video, GraphCuts, editing software, guests
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.
Links:
 http://cadik.posvete.cz/
http://cphoto.fit.vutbr.cz/
Progress assessment:
  
  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:
  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.