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dc.contributor.authorJu, Eunjungen_US
dc.contributor.authorKim, Kwang-yunen_US
dc.contributor.authorYoon, Sungjinen_US
dc.contributor.authorShim, Eungjuneen_US
dc.contributor.authorKang, Gyoo-Chulen_US
dc.contributor.authorChang, Phil Siken_US
dc.contributor.authorChoi, Myung Geolen_US
dc.contributor.editorBermano, Amit H.en_US
dc.contributor.editorKalogerakis, Evangelosen_US
dc.date.accessioned2024-04-16T14:39:38Z
dc.date.available2024-04-16T14:39:38Z
dc.date.issued2024
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.15027
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf15027
dc.description.abstractIn recent years, the fashion apparel industry has been increasingly employing virtual simulations for the development of new products. The first step in virtual garment simulation involves identifying the optimal simulation parameters that accurately reproduce the drape properties of the actual fabric. Recent techniques advocate for a data-driven approach, estimating parameters from outcomes of a Cusick drape test. Such methods deviate from standard Cusick drape tests, introducing high-cost tools, which reduces practicality. Our research presents a more practical model, utilizing 2D silhouette images from the ISO-standardized Cusick drape test. Notably, while past models have shown limitations in estimating stretching parameters, our novel approach leverages the fabric's tag information including fabric type and fiber composition. Our proposed model functions as a cascaded system: first, it estimates stretching parameters using tag information, then, in the subsequent step, it considers the estimated stretching parameters alongside the fabric sample's Cusick drape test results to determine bending parameters. We validated our model against existing methods and applied it in practical scenarios, showing promising outcomes.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies -> Neural networks; Physical simulation
dc.subjectComputing methodologies
dc.subjectNeural networks
dc.subjectPhysical simulation
dc.titleEstimating Cloth Simulation Parameters From Tag Information and Cusick Drape Testen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersCloth Simulation
dc.description.volume43
dc.description.number2
dc.identifier.doi10.1111/cgf.15027
dc.identifier.pages12 pages


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