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DC poleHodnotaJazyk
dc.contributor.authorTucholke, Marc-André
dc.contributor.authorChristoph, Marie
dc.contributor.authorAnders, Lasse
dc.contributor.authorOchlich, Raven
dc.contributor.authorGrogorick, Steve
dc.contributor.authorEisemann, Martin
dc.contributor.editorSkala, Václav
dc.date.accessioned2023-10-17T15:04:00Z
dc.date.available2023-10-17T15:04:00Z
dc.date.issued2023
dc.identifier.citationWSCG 2023: full papers proceedings: 1. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 168-175.en
dc.identifier.isbn978-80-86943-32-9
dc.identifier.issn2464–4617 (print)
dc.identifier.issn2464–4625 (CD/DVD)
dc.identifier.urihttp://hdl.handle.net/11025/54422
dc.description.sponsorship491805996 / GR 5932/1-1en
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.rights© Václav Skala - UNION Agencyen
dc.subjectodrazcs
dc.subjectbrýlecs
dc.subjectvideo konferencecs
dc.subjectzpracování obrazucs
dc.subjecthluboké učenícs
dc.subjectdetekce obličejecs
dc.subjectreálný čascs
dc.titleReal-Time Reflection Reduction from Glasses in Videoconferencesen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedSurrounding lighting conditions cannot always be sufficiently controlled during videoconferences, yielding situa tions in which disturbing reflections might appear on the participants glasses. In this article, we present a retrained neural network to convincingly reduce such reflections. For real time performance we propose an asynchronous processing pipeline accompanied by a head pose-based caching strategy to reuse intermediate processing results. The implementation as virtual webcam allows the system to be used with arbitrary videoconferencing systems.en
dc.subject.translatedreflectionen
dc.subject.translatedglassesen
dc.subject.translatedvideo conferencingen
dc.subject.translatedimage processingen
dc.subject.translateddeep learningen
dc.subject.translatedface detectionen
dc.subject.translatedreal timeen
dc.identifier.doihttps://www.doi.org/10.24132/CSRN.3301.20
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:WSCG 2023: Full Papers Proceedings

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Použijte tento identifikátor k citaci nebo jako odkaz na tento záznam: http://hdl.handle.net/11025/54422

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