In the last decade, computational photography has emerged as a vibrant field of research. A computational camera uses a combination of unconventional optics and novel algorithms to produce images that cannot otherwise be captured with traditional cameras. The design of such cameras involves the following two main aspects:
Examples of computational cameras that are already making an impact in the consumer market include: wide field-of-view (Omnicam), light-field (Lytro), high dynamic range (Red, Blackmagic Design), mobile (iPhone, Nexus), multispectral, motion sensing (Leap Motion) and depth cameras (Kinect).
This course serves as an introduction to the basic concepts in programmable optics and computational image processing needed for designing a wide variety of computational cameras, as well as an overview of the recent work in the field.
Mohit Gupta is an assistant professor in the CS department at the University of Wisconsin-Madison. Earlier, he was a research scientist in the CAVE lab at Columbia University. He received a B.Tech. in computer science from Indian Institute of Technology Delhi, and a Ph.D. from the Robotics Institute, Carnegie Mellon University. His research interests are broadly in computer vision and computational imaging. His focus is on designing computational cameras that enable computer vision systems to perform robustly in extreme real-world scenarios, as well as capture novel kinds of information about the physical world that is not possible with conventional cameras. Details can be found here.
Jean-François Lalonde is an assistant professor in ECE at Laval University, Quebec City. Previously, he was a Post-Doctoral Associate at Disney Research, Pittsburgh. He received a B.Eng. degree in Computer Engineering with honors from Laval University, Canada, in 2004. He earned his M.S at the Robotics Institute at Carnegie Mellon University in 2006 and received his Ph.D., also from Carnegie Mellon, in 2011. After graduation, he became a Computer Vision Scientist at Tandent, where he helped develop LightBrush™, the first commercial intrinsic imaging application. His work focuses on lighting-aware image understanding and synthesis by leveraging large amounts of data. Details can be found here.