Generating Pointillism Paintings Based on Seurat's Color Composition

dc.contributor.authorWu, Yi-Chianen_US
dc.contributor.authorTsai, Yu-Tingen_US
dc.contributor.authorLin, Wen-Chiehen_US
dc.contributor.authorLi, Wen-Hsinen_US
dc.contributor.editorNicolas Holzschuch and Szymon Rusinkiewiczen_US
dc.date.accessioned2015-02-28T15:38:08Z
dc.date.available2015-02-28T15:38:08Z
dc.date.issued2013en_US
dc.description.abstractThis paper presents a novel example-based stippling technique that employs a simple and intuitive concept to convert a color image into a pointillism painting. Our method relies on analyzing and imitating the color distributions of Seurat's paintings to obtain a statistical color model. Then, this model can be easily combined with the modified multi-class blue noise sampling to stylize an input image with characteristics of color composition in Seurat's paintings. The blue noise property of the output image also ensures that the color points are randomly located but remain spatially uniform. In our experiments, the multivariate goodness-of-fit tests were adopted to quantitatively analyze the results of the proposed and previous methods, further confirming that the color composition of our results are more similar to Seurat's painting style than that of previous approaches. Additionally, we also conducted a user study participated by artists to qualitatively evaluate the synthesized images of the proposed method.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.identifier.doi10.1111/cgf.12161en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12161en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.subjectI.4.10 [Image Processing and Computer Vision]en_US
dc.subjectImage Representationen_US
dc.subjectStatisticalen_US
dc.subjecten_US
dc.subjectJ.5 [Computer Applications]en_US
dc.subjectArts and Humanitiesen_US
dc.subjectFine artsen_US
dc.titleGenerating Pointillism Paintings Based on Seurat's Color Compositionen_US
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