Computation and Photography: How the Mobile Phone Became a Camera
The first camera phone was sold in 2000, when taking pictures with your phone was an oddity, and sharing pictures online was unheard-of. Today, barely twenty years later, the smartphone is more camera than phone. How did this happen? This transformation was enabled by advances in computational photography -- the science and engineering of making great images from small form factor, mobile cameras. Modern algorithmic and computing advances changed the rules of photography, bringing to it new modes of capture, post-processing, storage, and sharing, to make images ubiquitous across the world. In this talk, I'll describe some of the key elements of this technology, specifically those developed and launched recently by my team in several Google products.
Peyman leads the Computational Imaging team in Google Research, part of Google AI Perception. Prior to this, he was a Professor of Electrical Engineering at UC Santa Cruz from 1999-2014. He was Associate Dean for Research at the School of Engineering from 2010-12. From 2012-2014 he was on leave at Google-x, where he helped develop the imaging pipeline for Google Glass. Most recently, Peyman's team at Google developed the digital zoom pipeline for the Pixel phones, which includes the multi-frame super-resolution ("Super Res Zoom") pipeline, and the RAISR upscaling algorithm. In addition, the Night Sight mode on Pixel 3 uses our Super Res Zoom technology to merge images (whether you zoom or not) for vivid shots in low light.
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 holds 15 patents, several of which are commercially licensed. He founded MotionDSP, which was acquired by Cubic Inc. (NYSE:CUB).
Peyman has been keynote speaker at numerous technical conferences including Picture Coding Symposium (PCS), SIAM Imaging Sciences, SPIE, and the International Conference on Multimedia (ICME). Along with his students, he has won several best paper awards from the IEEE Signal Processing Society.
He is a Distinguished Lecturer of the IEEE Signal Processing Society, and a Fellow of the IEEE "for contributions to inverse problems and super-resolution in imaging."