Computational imaging uses unconventional optics to capture a coded image, and an appropriate algorithm to decode the captured image. This approach of manipulating images before there are recorded and processing recorded images before they are presented has three key benefits.
First, it enables us to implement imaging functionalities that would be difficult, if not impossible, to achieve using traditional imaging.
Second, it can be used to significantly reduce the hardware complexity of an imaging system.
Lastly, under appropriate imaging conditions, it allows us to break the limits of traditional imaging.
In this talk, I'll show recent examples of imaging systems that demonstrate these benefits. I'll conclude with a brief discussion on the fundamental limits of computational imaging.
There is no downloadable version of the slides for this talk available at this time.
About the speaker:
Shree K. Nayar received his PhD degree in Electrical and Computer Engineering from the Robotics Institute at Carnegie Mellon University in 1990. He is currently the T. C. Chang Professor of Computer Science at Columbia University. He co-directs the Columbia Vision and Graphics Center. He also heads the Columbia Computer Vision Laboratory (CAVE), which is dedicated to the development of advanced computer vision systems. His research is focused on three areas; the creation of novel cameras, the design of physics based models for vision, and the development of algorithms for scene understanding. His work is motivated by applications in the fields of digital imaging, computer graphics, and robotics.
He has received best paper awards at ICCV 1990, ICPR 1994, CVPR 1994, ICCV 1995, CVPR 2000, CVPR 2004 and ICCP 2010. He is the recipient of the David Marr Prize (1990 and 1995), the David and Lucile Packard Fellowship (1992), the National Young Investigator Award (1993), the NTT Distinguished Scientific Achievement Award (1994), the Keck Foundation Award for Excellence in Teaching (1995), the Columbia Great Teacher Award (in 2006), and the Carnegie Mellon Alumni Achievement Award (in 2009).
He was elected to the National Academy of Engineering in 2008 and to the American Academy of Arts and Sciences in 2011.
T. C. Chang Professor of Computer Science
New York City, New York