OAK

User, metric, and computational evaluation of foveated rendering methods

Metadata Downloads
Author(s)
Swafford, Nicholas T.Iglesias-Guitian, José A.Koniaris, CharalamposMoon, BochangCosker, DarrenMitchell, Kenny
Type
Conference Paper
Citation
ACM Symposium on Applied Perception, pp.7 - 14
Issued Date
2016-07-22
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.
Publisher
ASSOCIATION COMPUTING MACHINERY
Conference Place
US
Anaheim, California
URI
https://scholar.gist.ac.kr/handle/local/20595
공개 및 라이선스
  • 공개 구분공개
파일 목록
  • 관련 파일이 존재하지 않습니다.

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.