Humans see only a tiny region at the center of their visual field with the highest visual acuity, a behavior known
as foveation. Visual acuity reduces drastically towards the
visual periphery. ‘Foveated’ video coding/compression techniques exploit this non-uniformity to gain significant efficiency by compressing more in the periphery and less in the
center. We propose a practical and scalable method to use
such a technique for video streaming service over the Internet. The essential idea is to use a commodity webcam
on the user side to provide real-time gaze feedback to the
server with the server sending appropriately coded video to
the client player. We develop a multi-resolution video coding approach that is scalable in that it is possible to pre-code
the video in a small number of copies for a given set of resolutions. The coding approach is designed to match the error
performance of an eye tracker built using commodity webcams. We demonstrate that the technique is energy efficient
and thus usable in mobile devices. We develop a methodology for performance evaluation of such a system when network budgets may vary and video quality may fluctuate.
Finally, we present a comprehensive user study that demonstrates a bandwidth reduction of a factor of 2 for the same
user satisfaction.

Design and evaluation of a foveated video streaming service for commodity client devices

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