Lecture: Computational Photography

Course
- Lecturer(s):
- Start: April 7, 2014
- Dates: Mondays, 14:00 s.t., LBH - Room III.03
- Course number: MA-INF 2214
- Curriculum: Master
Exercises
- Tutor(s):
Description
We've set up a mailing list for scheduling the course and general communication. If you are interested in attending this course, Although the digital photography industry is expanding rapidly, most digital cameras still look and feel like film cameras, and they offer roughly the same set of features and controls. However, as sensors and in-camera processing systems improve, cameras and mobile devices are beginning to offer capabilities that film cameras never had. Among these are the ability to refocus photographs after they are taken (see the example above), or to combine views taken with different camera settings, aim, or placement. Equally exciting are new technologies for creating efficient, controllable illumination. Future "flashbulbs" may be pulsed LEDs or video projectors, with the ability to selectively illuminate objects, recolor the scene, or extract shape information. These developments force us to relax our notion of what constitutes "a photograph." They also blur the distinction between photography and scene modeling. These changes will lead to new photographic techniques, new scientific tools, and possibly new art forms. In this course, we will survey the converging technologies of digital photography, computational imaging, and image-based rendering, and we will explore the new imaging modalities that they enable. This is an advanced course for students with background in computer graphics or computer vision. The content is reflecting our conviction that successful researchers in this area must understand both the algorithms and the underlying technologies. The lectures may be accompanied by readings from textbooks or the research literature. These readings will be handed out in class or placed on the course web site. Students are expected to: An oral exam will conclude the course. Assignments will count 50% of the final grade, the exam will count the other 50%. Mailing list
please subscribe to the CompPhot list as soon as possible, so you will receive the latest updates.
About the course
Requirements
Tentative schedule
Date Topic 1 Mon, April 7 Introduction 2 Mon, April 14 Sensors 3 Mon, April 28 Optics 1 4 Mon, May 5 Optics 2 5 Mon, May 12 HDR and multi-spectral imaging 6 Mon, May 19 Signal processing basics 7 Mon, May 26 Deconvolution+Tomography 8 Mon, June 2 Ultrafast time-resolved imaging 9 Mon, June 16 Light fields 10 Mon, June 23 Apertures 11 Mon, June 30 Computational illumination and display 12 Mon, July 7 Project presentations
Slides
- Project topics (PDF document, 498 KB)
- Introduction (PDF document, 5.1 MB)
- Sensors (PDF document, 3.1 MB)
- Optics (PDF document, 4.6 MB)
- HDR-noise (PDF document, 3.0 MB)
- Panoramas (PDF document, 3.0 MB)
- SignalProcessing (PDF document, 2.4 MB)
- Inverse problems (PDF document, 1.9 MB)
- Light fields (PDF document, 3.1 MB)
- Reflectance fields (PDF document, 14.9 MB)
- Computational Illumination (PDF document, 3.9 MB)
Assignment Sheets
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Exercise 1: Assignment sheet (PDF document, 387 KB) |
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Exercise 2: Assignment sheet (PDF document, 184 KB)
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Exercise 3: Assignment sheet (PDF document, 223 KB)
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Exercise 4: Assignment sheet (PDF document, 134 KB) |
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Exercise 5: Assignment sheet (PDF document, 1.3 MB)
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Exercise 6: Assignment sheet (PDF document, 556 KB)
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