Please use this identifier to cite or link to this item: doi:10.22028/D291-38750
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Title: Foveated Depth-of-Field Filtering in Head-Mounted Displays
Author(s): Weier, Martin
Roth, Thorsten
Hinkenjann, André
Slusallek, Philipp
Language: English
Title: ACM Transactions on Applied Perception
Volume: 15
Issue: 4
Publisher/Platform: Association for Computing Machinery
Year of Publication: 2018
Free key words: Gaze-contingent depth-of-field
foveated rendering
ray tracing
eye-tracking
DDC notations: 004 Computer science, internet
Publikation type: Journal Article
Abstract: In recent years, a variety of methods have been introduced to exploit the decrease in visual acuity of peripheral vision, known as foveated rendering. As more and more computationally involved shading is requested and display resolutions increase, maintaining low latencies is challenging when rendering in a virtual reality context. Here, foveated rendering is a promising approach for reducing the number of shaded samples. However, besides the reduction of the visual acuity, the eye is an optical system, filtering radiance through lenses. The lenses create depth-of-field (DoF) effects when accommodated to objects at varying distances. The central idea of this article is to exploit these effects as a filtering method to conceal rendering artifacts. To showcase the potential of such filters, we present a foveated rendering system, tightly integrated with a gaze-contingent DoF filter. Besides presenting benchmarks of the DoF and rendering pipeline, we carried out a perceptual study, showing that rendering quality is rated almost on par with full rendering when using DoF in our foveated mode, while shaded samples are reduced by more than 69%.
DOI of the first publication: 10.1145/3238301
URL of the first publication: https://doi.org/10.1145/3238301
Link to this record: urn:nbn:de:bsz:291--ds-387503
hdl:20.500.11880/34911
http://dx.doi.org/10.22028/D291-38750
ISSN: 1544-3965
1544-3558
Date of registration: 18-Jan-2023
Description of the related object: Supplemental Material
Related object: https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3238301&file=weier.zip
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Professorship: MI - Prof. Dr. Philipp Slusallek
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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