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dc.contributor.authorZhao, Shuang
dc.contributor.authorDurand, Fredo
dc.contributor.authorZheng, Changxi
dc.date.accessioned2021-10-27T20:29:03Z
dc.date.available2021-10-27T20:29:03Z
dc.date.issued2018
dc.identifier.urihttps://hdl.handle.net/1721.1/135737
dc.description.abstract© 1995-2012 IEEE. The inverse diffusion curve problem focuses on automatic creation of diffusion curve images that resemble user provided color fields. This problem is challenging since the 1D curves have a nonlinear and global impact on resulting color fields via a partial differential equation (PDE). We introduce a new approach complementary to previous methods by optimizing curve geometry. In particular, we propose a novel iterative algorithm based on the theory of shape derivatives. The resulting diffusion curves are clean and well-shaped, and the final image closely approximates the input. Our method provides a user-controlled parameter to regularize curve complexity, and generalizes to handle input color fields represented in a variety of formats.
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.isversionof10.1109/TVCG.2017.2721400
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourcearXiv
dc.titleInverse Diffusion Curves using Shape Optimization
dc.typeArticle
dc.identifier.citationShuang, Zhao, F. Durand, and Zheng Changxi. "Inverse Diffusion Curves Using Shape Optimization [Arxiv]." arXiv (2016): 14 pp.
dc.relation.journalIEEE Transactions on Visualization and Computer Graphics
dc.eprint.versionOriginal manuscript
dc.type.urihttp://purl.org/eprint/type/JournalArticle
eprint.statushttp://purl.org/eprint/status/NonPeerReviewed
dc.date.updated2019-05-29T13:29:43Z
dspace.orderedauthorsZhao, S; Durand, F; Zheng, C
dspace.date.submission2019-05-29T13:29:44Z
mit.journal.volume24
mit.journal.issue7
mit.metadata.statusAuthority Work and Publication Information Needed


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