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DTSTAMP:20230103T035307Z
LOCATION:Auditorium\, Level 5\, West Wing
DTSTART;TZID=Asia/Seoul:20221206T100000
DTEND;TZID=Asia/Seoul:20221206T120000
UID:siggraphasia_SIGGRAPH Asia 2022_sess153_papers_473@linklings.com
SUMMARY:Progressive Simulation for Cloth Quasistatics
DESCRIPTION:Technical Papers\n\nProgressive Simulation for Cloth Quasistat
 ics\n\nZhang, Dumas, Fei, Jacobson, James...\n\nThe trade-off between spee
 d and fidelity in cloth simulation is a fundamental computational problem 
 in computer graphics and computational design. Coarse cloth models provide
  the interactive performance required by designers, but they can not be si
 mulated at higher resolutions (``up-resed'') without introducing simulatio
 n artifacts and/or unpredicted outcomes, such as different folds, wrinkles
  and drapes.  But how can a coarse simulation predict the result of an unc
 onstrained, high-resolution simulation that has not yet been run?\n\nWe 
 propose Progressive Cloth Simulation (PCS), a new forward simulation metho
 d for efficient preview of cloth quasistatics on exceedingly coarse triang
 le meshes with consistent and progressive improvement over a hierarchy of 
 increasingly higher-resolution models.  PCS provides an efficient coarse p
 reviewing simulation method that predicts the coarse-scale folds and wrink
 les that will be generated by a corresponding converged, high-fidelity C-I
 PC simulation of the cloth drape's equilibrium. For each preview PCS can g
 enerate an increasing-resolution sequence of consistent models that progre
 ss towards this converged solution. This successive improvement can then b
 e interrupted at any point, for example, whenever design parameters are up
 dated. PCS then ensures feasibility at all resolutions, so that predicted 
 solutions remain intersection-free and capture the complex folding and buc
 kling behaviors of frictionally contacting cloth.\n\nRegistration Category
 : FULL ACCESS, EXPERIENCE PLUS ACCESS, EXPERIENCE ACCESS, TRADE EXHIBITOR\
 n\nLanguage: ENGLISH\n\nFormat: IN-PERSON
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_473&sess=sess15
 3
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