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dc.contributor.authorHsiao, Kai-Wenen_US
dc.contributor.authorYang, Yong-Liangen_US
dc.contributor.authorChiu, Yung-Chihen_US
dc.contributor.authorHu, Min-Chunen_US
dc.contributor.authorYao, Chih-Yuanen_US
dc.contributor.authorChu, Hung-Kuoen_US
dc.contributor.editorMyszkowski, Karolen_US
dc.contributor.editorNiessner, Matthiasen_US
dc.date.accessioned2023-05-03T06:09:28Z
dc.date.available2023-05-03T06:09:28Z
dc.date.issued2023
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14742
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14742
dc.description.abstractLogos are one of the most important graphic design forms that use an abstracted shape to clearly represent the spirit of a community. Among various styles of abstraction, a particular golden-ratio design is frequently employed by designers to create a concise and regular logo. In this context, designers utilize a set of circular arcs with golden ratios (i.e., all arcs are taken from circles whose radii form a geometric series based on the golden ratio) as the design elements to manually approximate a target shape. This error-prone process requires a large amount of time and effort, posing a significant challenge for design space exploration. In this work, we present a novel computational framework that can automatically generate golden ratio logo abstractions from an input image. Our framework is based on a set of carefully identified design principles and a constrained optimization formulation respecting these principles. We also propose a progressive approach that can efficiently solve the optimization problem, resulting in a sequence of abstractions that approximate the input at decreasing levels of detail. We evaluate our work by testing on images with different formats including real photos, clip arts, and line drawings. We also extensively validate the key components and compare our results with manual results by designers to demonstrate the effectiveness of our framework. Moreover, our framework can largely benefit design space exploration via easy specification of design parameters such as abstraction levels, golden circle sizes, etc.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies -> Computer Graphics
dc.subjectComputing methodologies
dc.subjectComputer Graphics
dc.titleImg2Logo: Generating Golden Ratio Logos from Imagesen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersLogos and Clip-Art
dc.description.volume42
dc.description.number2
dc.identifier.doi10.1111/cgf.14742
dc.identifier.pages37-49
dc.identifier.pages13 pages


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