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dc.contributor.authorDenes, G
dc.contributor.authorJindal, A
dc.contributor.authorMikhailiuk, A
dc.contributor.authorMantiuk, RK
dc.date.accessioned2020-05-11T13:27:32Z
dc.date.available2020-05-11T13:27:32Z
dc.date.issued2020
dc.identifier.issn0730-0301
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/305189
dc.description.abstract<jats:p>Limited GPU performance budgets and transmission bandwidths mean that real-time rendering often has to compromise on the spatial resolution or temporal resolution (refresh rate). A common practice is to keep either the resolution or the refresh rate constant and dynamically control the other variable. But this strategy is non-optimal when the velocity of displayed content varies. To find the best trade-off between the spatial resolution and refresh rate, we propose a perceptual visual model that predicts the quality of motion given an object velocity and predictability of motion. The model considers two motion artifacts to establish an overall quality score: non-smooth (juddery) motion, and blur. Blur is modeled as a combined effect of eye motion, finite refresh rate and display resolution. To fit the free parameters of the proposed visual model, we measured eye movement for predictable and unpredictable motion, and conducted psychophysical experiments to measure the quality of motion from 50 Hz to 165 Hz. We demonstrate the utility of the model with our on-the-fly motion-adaptive rendering algorithm that adjusts the refresh rate of a G-Sync-capable monitor based on a given rendering budget and observed object motion. Our psychophysical validation experiments demonstrate that the proposed algorithm performs better than constant-refresh-rate solutions, showing that motion-adaptive rendering is an attractive technique for driving variable-refresh-rate displays.</jats:p>
dc.publisherAssociation for Computing Machinery (ACM)
dc.rightsAll rights reserved
dc.titleA perceptual model of motion quality for rendering with adaptive refresh-rate and resolution
dc.typeArticle
prism.issueIdentifier4
prism.publicationDate2020
prism.publicationNameACM Transactions on Graphics
prism.volume39
dc.identifier.doi10.17863/CAM.52275
dcterms.dateAccepted2020-05-01
rioxxterms.versionofrecord10.1145/3386569.3392411
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2020-07-08
dc.contributor.orcidJindal, Akshay [0000-0003-0557-0726]
dc.contributor.orcidMikhailiuk, Aliaksei [0000-0001-9757-6644]
dc.contributor.orcidMantiuk, Rafal [0000-0003-2353-0349]
dc.identifier.eissn1557-7368
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEuropean Research Council (725253)
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Marie Sklodowska-Curie actions (765911)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/N509620/1)
pubs.funder-project-idEngineering and Physical Sciences Research Council (1778303)
cam.orpheus.successTue Sep 01 09:02:40 BST 2020 - Embargo updated
cam.orpheus.counter17
rioxxterms.freetoread.startdate2020-12-31


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