Greedy Image Approximation for Artwork Generation via Contiguous Bézier Segments

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dc.contributor.authorNehring-Wirxel, Juliusen_US
dc.contributor.authorLim, Isaaken_US
dc.contributor.authorKobbelt, Leifen_US
dc.contributor.editorGuthe, Michaelen_US
dc.contributor.editorGrosch, Thorstenen_US
dc.date.accessioned2023-09-25T11:38:21Z
dc.date.available2023-09-25T11:38:21Z
dc.date.issued2023
dc.description.abstractThe automatic creation of digital art has a long history in computer graphics. In this work, we focus on approximating input images to mimic artwork by the artist Kumi Yamashita, as well as the popular scribble art style. Both have in common that the artists create the works by using a single, contiguous thread (Yamashita) or stroke (scribble) that is placed seemingly at random when viewed at close range, but perceived as a tone-mapped picture when viewed from a distance. Our approach takes a rasterized image as input and creates a single, connected path by iteratively sampling a set of candidate segments that extend the current path and greedily selecting the best one. The candidates are sampled according to art style specific constraints, i.e. conforming to continuity constraints in the mathematical sense for the scribble art style. To model the perceptual discrepancy between close and far viewing distances, we minimize the difference between the input image and the image created by rasterizing our path after applying the contrast sensitivity function, which models how human vision blurs images when viewed from a distance. Our approach generalizes to colored images by using one path per color. We evaluate our approach on a wide range of input images and show that it is able to achieve good results for both art styles in grayscale and color.en_US
dc.description.sectionheadersImage Processing
dc.description.seriesinformationVision, Modeling, and Visualization
dc.identifier.doi10.2312/vmv.20231234
dc.identifier.isbn978-3-03868-232-5
dc.identifier.pages123-131
dc.identifier.pages9 pages
dc.identifier.urihttps://doi.org/10.2312/vmv.20231234
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vmv20231234
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Non-photorealistic rendering; Applied computing → Media arts
dc.subjectComputing methodologies → Non
dc.subjectphotorealistic rendering
dc.subjectApplied computing → Media arts
dc.titleGreedy Image Approximation for Artwork Generation via Contiguous Bézier Segmentsen_US
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