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dc.contributor.authorHalter, Gaudenzen_US
dc.contributor.authorBallester-Ripoll, Rafaelen_US
dc.contributor.authorFlueckiger, Barbaraen_US
dc.contributor.authorPajarola, Renatoen_US
dc.contributor.editorGleicher, Michael and Viola, Ivan and Leitte, Heikeen_US
dc.date.accessioned2019-06-02T18:27:30Z
dc.date.available2019-06-02T18:27:30Z
dc.date.issued2019
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.13676
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13676
dc.description.abstractWhile color plays a fundamental role in film design and production, existing solutions for film analysis in the digital humanities address perceptual and spatial color information only tangentially. We introduce VIAN, a visual film annotation system centered on the semantic aspects of film color analysis. The tool enables expert-assessed labeling, curation, visualization and classification of color features based on their perceived context and aesthetic quality. It is the first of its kind that incorporates foreground-background information made possible by modern deep learning segmentation methods. The proposed tool seamlessly integrates a multimedia data management system, so that films can undergo a full color-oriented analysis pipeline.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectVisualization systems and tools
dc.subjectApplied computing
dc.subjectMedia arts
dc.titleVIAN: A Visual Annotation Tool for Film Analysisen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersAnalysis Applications and Systems
dc.description.volume38
dc.description.number3
dc.identifier.doi10.1111/cgf.13676
dc.identifier.pages119-129


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  • 38-Issue 3
    EuroVis 2019 - Conference Proceedings

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