Computational photography: advanced topics

Computational photography combines plentiful computing, digital sensors, modern optics, many varieties of actuators, probes and smart lights to escape the limitations of traditional film cameras and enables novel imaging applications. Unbounded dynamic range, variable focus, resolution, and depth of field, hints about shape, reflectance, and lighting, and new interactive forms of photos that are partly snapshots and partly videos, performance capture and interchangeably relighting real and virtual characters are just some of the new applications emerging in Computational Photography. The computational techniques encompass methods from modification of imaging parameters during capture to sophisticated reconstructions from indirect measurements.

We will bypass basic and introductory material presented in earlier versions of this course (Computational Photography 2005, 6, 7) and expand coverage of more recent topics. Emphasizing more recent work in computational photography and related fields (2006 or later) this course will give more attention to advanced topics only briefly touched before, including tomography, heterodyning and Fourier Slice applications, inverse problems, gradient illumination, novel optics, emerging sensors and social impact of computational photography. With this deeper coverage, the course offers a diverse but practical guide to topics in image capture and manipulation methods for generating compelling pictures for computer graphics and for extracting scene properties for computer vision, with several examples.