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Anti-aliasing Techniques in Virtual Reality: A User Study with Perceptual Pairwise Comparison Ranking Scheme

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dc.contributor.authorWaldow, Kristoffer
dc.contributor.authorScholz, Jonas
dc.contributor.authorMisiak, Martin
dc.contributor.authorFuhrmann, Arnulph
dc.contributor.authorRoth, Daniel
dc.contributor.authorLatoschik, Marc Erich
dc.date.accessioned2024-09-03T13:00:44Z
dc.date.available2024-09-03T13:00:44Z
dc.date.issued2024
dc.description.abstractAnti-aliasing is essential for Virtual Reality (VR) applications, as the pixels of current VR displays subtend a large field of view. This makes various undersampling artifacts particularly noticeable. Un- derstanding state-of-the-art anti-aliasing techniques and their trade- offs is therefore crucial for optimizing VR experiences and develop- ing high-quality VR applications. This paper investigates multiple anti-aliasing techniques through a user study with pairwise compar- isons to determine the best method for image quality in VR, con- sidering both static and moving objects in four different plausible environments. Results indicate that the ranking of methods does not differ significantly between moving and static scenes. While naive Supersampling Anti-Aliasing provides the best image qual- ity from the tested methods and Fast Approximate Anti-Aliasing the worst, Temporal Anti-Aliasing and Multisample Anti-Aliasing achieved similar results in terms of image quality.en
dc.identifier.doi10.18420/vrar2024_0015
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/44475
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofGI VR / AR Workshop
dc.titleAnti-aliasing Techniques in Virtual Reality: A User Study with Perceptual Pairwise Comparison Ranking Schemeen
dc.typeText/Workshop Paper
gi.conference.date17. - 18. September 2024

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