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dc.contributor.authorGao, Chengyingen_US
dc.contributor.authorTang, Mengyueen_US
dc.contributor.authorLiang, Xiangguoen_US
dc.contributor.authorSu, Zhuoen_US
dc.contributor.authorZou, Changqingen_US
dc.contributor.editorChen, Min and Benes, Bedrichen_US
dc.date.accessioned2018-09-19T15:32:51Z
dc.date.available2018-09-19T15:32:51Z
dc.date.issued2018
dc.identifier.issn1467-8659
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13334
dc.identifier.urihttps://doi.org/10.1111/cgf.13334
dc.description.abstractNon‐photorealistic rendering has been an active area of research for decades whereas few of them concentrate on rendering chromatic penciling style. In this paper, we present a framework named as PencilArt for the chromatic penciling style generation from wild photographs. The structural outline and textured map for composing the chromatic pencil drawing are generated, respectively. First, we take advantage of deep neural network to produce the structural outline with proper intensity variation and conciseness. Next, for the textured map, we follow the painting process of artists to adjust the tone of input images to match the luminance histogram and pencil textures of real drawings. Eventually, we evaluate PencilArt via a series of comparisons to previous work, showing that our results better capture the main features of real chromatic pencil drawings and have an improved visual appearance.Non‐photorealistic rendering has been an active area of research for decades whereas few of them concentrate on rendering chromatic penciling style. In this paper, we present a framework named as PencilArt for the chromatic penciling style generation from wild photographs. The structural outline and textured map for composing the chromatic pencil drawing are generated, respectively. First, we take advantage of deep neural network to produce the structural outline with proper intensity variation and conciseness. Next, for the textured map, we follow the painting process of artists to adjust the tone of input images to match the luminance histogram and pencil textures of real drawings. Eventually, we evaluate PencilArt via a series of comparisons to previous work, showing that our results better capture the main features of real chromatic pencil drawings and have an improved visual appearance.en_US
dc.publisher© 2018 The Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectnon‐photorealistic rendering
dc.subjectimage/video editing
dc.subjectimage processing
dc.subjectI.4.9 [Image Processing and Computer Vision]: Applications—
dc.titlePencilArt: A Chromatic Penciling Style Generation Frameworken_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersArticles
dc.description.volume37
dc.description.number6
dc.identifier.doi10.1111/cgf.13334
dc.identifier.pages395-409


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