Collaborative Research: CNS Core: HCC: Small: Enabling Efficient Computer Systems for Augmented and Virtual Reality: A Perception-Guided Approach

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This research project designs software-hardware collaborative mechanisms to bridge the gap between human visual perception and augmented/virtual reality (AR/VR) systems design and ultimately deliver an order of magnitude efficiency gains. Achieving this goal requires first developing computational models to quantitatively capture human visual perception, and then investigating new techniques across the systems stack that leverage the perceptual models for efficient processing. The intellectual merit of the project is the pursuit of three classes of techniques pertaining to exploiting unique characteristics of human perception to build efficient AR/VR systems: 1) identify key aspects of visual stimuli that simultaneously influence viewing experience and system efficiency and investigate lightweight modeling strategies through extensive psychophysical experiments, 2) investigate enabling techniques across the entire application pipeline (from algorithms and systems to the display) that leverage the perceptual models for improving system efficiency, and 3) develop a data-driven, learning-based approach to tune the entire system while satisfying perceptual and efficiency requirements.The research agenda is complemented by an educational/outreach agenda. The PIs will (1) offer summer research and programming opportunities to high school students in Rochester and New York, (2) introduce new courses/modules in both University of Rochester and NYU on visual perception and its connection to computer systems design, (3) reach out and collaboration with industry partners to explore technology transfer possibilities, and (4) offer undergraduate students inclusive opportunities for hands-on experience in emerging application domains and hardware acceleration. Broadly, the integrated research and education activities will lead the way to an explosion of new products and ideas, which in turn addresses key technological and societal issues in areas such as healthcare, education, remote communication and interaction, professional training, and industrial design.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.