15. Computational Photography

Monday
Half Day, 8:30 am - 12:15 pm
Level: Intermediate
Room 258

Computational methods for overcoming the traditional limitations of a camera and enabling novel imaging applications. The course provides a 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.

Prerequisites
A basic understanding of camera operation and image processing. Familiarity with concepts of linear systems, convolution, and machine vision is useful.

Intended Audience
Photographers, digital artists, image processing programmers and vision researchers who use or build applications for digital cameras or images will learn about camera fundamentals and powerful computational tools, with many real-world examples.

Co-Organizers
Ramesh Raskar
Mitsubishi Electric Research Laboratories (MERL)

Jack Tumblin
Northwestern University

Lecturers
Marc Levoy
Stanford University

Shree Nayar
Columbia University