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DTSTAMP:20260817T171516Z
LOCATION:Hall C\, C Block\, Level 4
DTSTART;TZID=Asia/Tokyo:20241203T090000
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UID:siggraphasia_SIGGRAPH Asia 2024_sess223_papers_379@linklings.com
SUMMARY:Volumetric Homogenization for Knitwear Simulation
DESCRIPTION:Chun Yuan, Haoyang Shi, and Lei Lan (University of Utah); Yuxi
 ng Qiu (LightSpeed Studios); Cem Yuksel (University of Utah); Huamin Wang 
 (Style3D Research); Chenfanfu Jiang (University of California Los Angeles)
 ; Kui Wu (LightSpeed Studios); and Yin Yang (University of Utah)\n\nWe pre
 sent volumetric homogenization,  a spatially varying homogenization scheme
  for knitwear simulation. We are motivated by the observation that macro-s
 cale fabric dynamics is strongly correlated with its underlying knitting p
 atterns. Therefore, homogenization towards a single\nmaterial is less effe
 ctive when the knitting is complex and non-repetitive. Our method tackles 
 this challenge by homogenizing the yarn-level material locally at volumetr
 ic elements. Assigning a virtual volume of a knitting structure enables us
  to model bending and twisting effects via a simple volume-preserving pena
 lty and thus effectively alleviates the material nonlinearity. We employ a
 n adjoint Gauss-Newton formulation[Zehnder et al. 2021] to battle the dime
 nsionality challenge of such per-element material optimization. This intui
 tive material model makes the forward simulation GPU-friendly. To this end
 , our pipeline also equips a novel domain-decomposed subspace solver craft
 ed for GPU projective dynamics, which makes our simulator\nhundreds of tim
 es faster than the yarn-level simulator. Experiments validate the capabili
 ty and effectiveness of volumetric homogenization. Our method produces rea
 listic animations of knitwear matching the quality of full-scale yarn-leve
 l simulations. It is also orders of magnitude faster than existing homogen
 ization techniques in both the training and simulation stages.\n\nRegistra
 tion Category: Enhanced Access, Full Access, Full Access Supporter\n\nLang
 uage Format: English Language\n\n
URL:https://asia.siggraph.org/2024/program/?id=papers_379&sess=sess118
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