WS2020/21 – Computational Photography MA-INF 2214

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 survey the converging technologies of digital photography, computational imaging, and image-based rendering, and we will explore the new imaging modalities that they enable.

Lecturers

    • Prof. Dr. Matthias Hullin
    • M.Sc. Clara Callenberg

Winter 2020/21 – COURSE CANCELLED

This year, the Computational Photography course cannot be held due to coronavirus limitations. Its strong focus on group-based learning and hands-on lab work cannot reasonably be replaced by online offerings. We look forward to welcoming you in a future iteration of the course.

Requirements

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 practical assignments (including a course project to be prepared and presented in teams).
An oral exam will conclude the course.