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dc.contributor.authorWei, Guangshunen_US
dc.contributor.authorZhou, Yuanfengen_US
dc.contributor.authorGao, Xifengen_US
dc.contributor.authorMa, Qianen_US
dc.contributor.authorXin, Shiqingen_US
dc.contributor.authorHe, Yingen_US
dc.contributor.editorLee, Jehee and Theobalt, Christian and Wetzstein, Gordonen_US
dc.description.abstractImage vectorization is an important yet challenging problem, especially when the input image has rich content. In this paper, we develop a novel method for automatically vectorizing natural images with feature-aligned quad-dominant meshes. Inspired by the quadrangulation methods in 3D geometry processing, we propose a new directional field optimization technique by encoding the color gradients, sidestepping the explicit computing of salient image features. We further compute the anisotropic scales of the directional field by accommodating the distance among image features. Our method is fully automatic and efficient, which takes only a few seconds for a 400x400 image on a normal laptop. We demonstrate the effectiveness of the proposed method on various image editing applications.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.3 [Computer Graphics]
dc.subjectImage processing
dc.titleField-aligned Quadrangulation for Image Vectorizationen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersImage Processing

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  • 38-Issue 7
    Pacific Graphics 2019 - Symposium Proceedings

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