Vorlesung: Computational Photography


  • Dozent(en):
  • Beginn: April 7, 2014
  • Zeiten: Montags 14:00 s.t., LBH - Hörsaal III.03
  • Veranstaltungsnummer: MA-INF 2214
  • Studiengang: Master



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About the 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:

  1. attend the lectures, and participate in class discussions
  2. complete the assignments
  3. prepare and present a course project

An oral exam will conclude the course. Assignments will count 50% of the final grade, the exam will count the other 50%.

Tentative schedule

1Mon, April 7Introduction
2Mon, April 14Sensors
3Mon, April 28Optics 1
4Mon, May 5Optics 2
5Mon, May 12HDR and multi-spectral imaging
6Mon, May 19Signal processing basics
7Mon, May 26Deconvolution+Tomography
8Mon, June 2Ultrafast time-resolved imaging
9Mon, June 16Light fields
10Mon, June 23Apertures
11Mon, June 30Computational illumination and display
12Mon, July 7Project presentations



Übung 1:
Übungsblatt  (PDF-Dokument, 387 KB)
Übung 2:
Übungsblatt  (PDF-Dokument, 184 KB)
Übung 3:
Übungsblatt  (PDF-Dokument, 223 KB)
Übung 4:
Übungsblatt  (PDF-Dokument, 134 KB)
Übung 5:
Übungsblatt  (PDF-Dokument, 1.3 MB)
Übung 6:
Übungsblatt  (PDF-Dokument, 556 KB)