User, Metric, and Computational Evaluation of Foveated Rendering Methods

Nicholas Swafford, Jose A Iglesias_Guitian, Charalampos Koniaris, Bochang Moon, Darren Cosker, Kenny Mitchell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Citations (Scopus)
114 Downloads (Pure)

Abstract

Perceptually lossless foveated rendering methods exploit human perception by selectively rendering at different quality levels based on eye gaze (at a lower computational cost) while still maintaining the user's perception of a full quality render. We consider three foveated rendering methods and propose practical rules of thumb for each method to achieve significant performance gains in real-time rendering frameworks. Additionally, we contribute a new metric for perceptual foveated rendering quality building on HDR-VDP2 that, unlike traditional metrics, considers the loss of fidelity in peripheral vision by lowering the contrast sensitivity of the model with visual eccentricity based on the Cortical Magnification Factor (CMF). The new metric is parameterized on user-test data generated in this study. Finally, we run our metric on a novel foveated rendering method for real-time immersive 360° content with motion parallax.
Original languageEnglish
Title of host publicationSAP '16 Proceedings of the ACM Symposium on Applied Perception
PublisherAssociation for Computing Machinery
Pages7-14
Number of pages8
ISBN (Electronic)9781450343831
DOIs
Publication statusPublished - 22 Jul 2016

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