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DC poleHodnotaJazyk
dc.contributor.authorDel Gallego, Neil Patrick
dc.contributor.authorViaje, Cedric Lance
dc.contributor.authorGerra-Clarin, Michael Ryan
dc.contributor.authorRoque, John Marvic
dc.contributor.authorNon, Gary Steven
dc.contributor.authorMartinez, Jesin Jarod
dc.contributor.authorGana, Jose Antonio
dc.contributor.editorSkala, Václav
dc.date.accessioned2021-08-31T06:44:51Z
dc.date.available2021-08-31T06:44:51Z
dc.date.issued2021
dc.identifier.citationWSCG 2021: full papers proceedings: 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 81-90.en
dc.identifier.isbn978-80-86943-34-3
dc.identifier.issn2464-4617
dc.identifier.issn2464–4625(CD/DVD)
dc.identifier.urihttp://hdl.handle.net/11025/45012
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.rights© Václav Skala - UNION Agencycs
dc.subjectrozšířená realitacs
dc.subjectmobilní zařízenícs
dc.subjectobrazový filtrcs
dc.subjectstylizace obrazucs
dc.subjectpřenos stylucs
dc.subjectmalířské ztvárněnícs
dc.titleA Mobile Augmented Reality Application For Simulating Claude Monet’s Impressionistic Art Styleen
dc.typeconferenceObjecten
dc.typekonferenční příspěvekcs
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedIn this study, we showcase a mobileaugmented reality application where a user places various 3D models in atabletop scene. The scene is captured and then rendered as Claude Monet’s impressionistic art style. One possibleuse case for this application is to demonstrate the behavior of the impressionistic art style of Claude Monet, byapplying this to tabletop scenes, which can be useful especially for art students. This allows the user to create theirown "still life" composition and study how the scene is painted. Our proposed framework is composed of threesteps. The system first identifies the context of the tabletop scene, through GIST descriptors, which are used asfeatures to identify the color palette to be used for painting. Our application supports three different color palettes,representing different eras of Monet’s work. The second step performs color mixing of two different colors in thechosen palette. The last step involves applying a three-stage brush stroke algorithm where the image is renderedwith a customized brush stroke pattern applied in each stage. While deep learning techniques are already capableof performing style transfer from paintings to real-world images, such as the success of CycleGAN, results showthat our proposed framework achieves comparable performance to deep learning style transfer methods on tabletopscenes.en
dc.subject.translatedaugmented realityen
dc.subject.translatedmobile devicesen
dc.subject.translatedimage filteren
dc.subject.translatedimage stylizationen
dc.subject.translatedstyle transferen
dc.subject.translatedpainterly renderingen
dc.identifier.doihttps://doi.org/10.24132/CSRN.2021.3101.9
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:WSCG 2021: Full Papers Proceedings

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