Title: | Computational Photography |
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Code: | VYF |
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Ac.Year: | 2017/2018 |
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Term: | Summer |
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Curriculums: | |
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Language of Instruction: | Czech |
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Credits: | 5 |
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Completion: | classified credit |
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Type of instruction: | Hour/sem | Lectures | Sem. Exercises | Lab. exercises | Comp. exercises | Other |
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Hours: | 26 | 0 | 0 | 0 | 26 |
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| Examination | Tests | Exercises | Laboratories | Other |
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Points: | 0 | 40 | 0 | 0 | 60 |
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Guarantor: | Čadík Martin, doc. Ing., Ph.D., DCGM |
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Lecturer: | Čadík Martin, doc. Ing., Ph.D., DCGM |
Faculty: | Faculty of Information Technology BUT |
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Department: | Department of Computer Graphics and Multimedia FIT BUT |
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Schedule: | Day | Lesson | Week | Room | Start | End | Lect.Gr. | St.G. | EndG. |
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Wed | příprava VYF | lectures | E104 | 11:00 | 11:50 | | | |
Wed | lecture | lectures | E104 | 12:00 | 13:50 | 1MIT | xx | xx |
Wed | lecture | lectures | E104 | 12:00 | 13:50 | 2MIT | xx | xx |
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| Learning objectives: |
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| | 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: |
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| | 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: |
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| - introduction to CP, light and color (slides, projects, final report template)
- photography, optics, physics, sensors, noise (slides)
- visual perception, natural image statistics (slides)
- image blending (slides)
- Color, color spaces, color transfer, color-to-grayscale image conversions (slides)
- High dynamic range (HDR) imaging - acquisition, storage and display (slides, HDR)
- High dynamic range (HDR) imaging - tone mapping, inverse tone mapping (slides)
- Image registration for computational photography (slajdy, pano Canon, pano Ricoh)
- Computational illumination, dual photography, illumination changes (slajdy)
- Image and video quality metrics (slides)
- Omnidirectional camera, lightfields, synthetic aperture
- Non-photorealistic camera, computational aesthetics
- Computational video, GraphCuts, editing software, guests
| Fundamental literature: |
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| - 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: |
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| http://cadik.posvete.cz/ http://cphoto.fit.vutbr.cz/
| Progress assessment: |
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| | - Project proposals
- Project assignments
- Consultations after the lecture - literature
- Consultations after the lecture - implementation
- Consultations after the lecture - testing
- WRITTEN EXAM
- Finished implementations
- Presentations of assignments, final reports
| Exam prerequisites: |
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| | 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.
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