Computational Imaging: From Photons to Photos

Peyman Milanfar

Peyman Milanfar


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Date: April 15, 2015


Fancy cameras used to be the exclusive domain of professional photographers and experimental scientists. Times have changed, but even as recently as a decade ago, consumer cameras were solitary pieces of hardware and glass; disconnected gadgets with little brains, and no software. But now, everyone owns a smartphone with a powerful processor, and every smartphone has a camera. These mobile cameras are simple, costing only a few dollars per unit. And on their own, they are no competition for their more expensive cousins. But coupled with the processing power native to the devices in which they sit, they are so effective that much of the low-end point-and-shoot camera market has already been decimated by mobile photography. Computational imaging is the enabler for this new paradigm in consumer photography. It is the art, science, and engineering of producing a great shot (moving or still) from small form factor, mobile cameras. It does so by changing the rules of image capture — recording information in space, time, and across other degrees of freedom — while relying heavily on post-processing to produce a final result. Ironically, in this respect, mobile imaging devices are now more like scientific instruments than conventional cameras. This has deep implications for the future of consumer photography. In this technological landscape, the ubiquity of devices and open platforms for imaging will inevitably lead to an explosion of technical and economic activity, as was the case with other types of mobile applications. Meanwhile, clever algorithms, along with dedicated hardware architectures, will take center stage and enable unprecedented imaging capabilities in the user’s hands.

Further Information:

Peyman received his undergraduate education in electrical engineering and mathematics from the University of California, Berkeley, and the MS and PhD degrees in electrical engineering from the Massachusetts Institute of Technology. He was a Professor of EE at UC Santa Cruz from 1999-2014, having served as Associate Dean of the School of Engineering from 2010-12. From 2012-2014 he was at Google-x, where he helped develop the imaging pipeline for Google Glass. He currently leads the Computational Imaging team in Google Research. He holds 8 US patents; has been keynote speaker at numerous conferences including PCS, SPIE, and ICME; and along with his students, won several best paper awards from the IEEE Signal Processing Society. He is a Fellow of the IEEE.

Created: Wednesday, April 15th, 2015