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DTSTAMP:20260114T163633Z
LOCATION:Darling Harbour Theatre\, Level 2 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231212T093000
DTEND;TZID=Australia/Melbourne:20231212T124500
UID:siggraphasia_SIGGRAPH Asia 2023_sess209_tog_102@linklings.com
SUMMARY:Digital 3D Smocking Design
DESCRIPTION:Jing Ren, Aviv Segall, and Olga Sorkine-Hornung (ETH Zürich)\n
 \nWe develop an optimization-based method to model smocking, a surface emb
 roidery technique that provides decorative geometric texturing while maint
 aining stretch properties of the fabric. During smocking, multiple pairs o
 f points on the fabric are stitched together, creating non-manifold geomet
 ric features and visually pleasing textures. Designing smocking patterns i
 s challenging, because the outcome of stitching is unpredictable: the fina
 l texture is often revealed only when the whole smocking process is comple
 ted, necessitating painstaking physical fabrication and time consuming tri
 al-and-error experimentation. This motivates us to seek a digital smocking
  design method. Straightforward attempts to compute smocked fabric geometr
 y using surface deformation or cloth simulation methods fail to produce re
 alistic results, likely due to the intricate structure of the designs, the
  large number of contacts and high-curvature folds. We instead formulate s
 mocking as a graph embedding and shape deformation problem. We extract a c
 oarse graph representing the fabric and the stitching constraints, and the
 n derive the graph structure of the smocked result. We solve for the 3D em
 bedding of this graph, which in turn reliably guides the deformation of th
 e high-resolution fabric mesh. Our optimization based method is simple, ef
 ficient, and flexible, which allows us to build an interactive system for 
 smocking pattern exploration. To demonstrate the accuracy of our method, w
 e compare our results to real fabrications on a large set of smocking patt
 erns.\n\nRegistration Category: Full Access, Enhanced Access, Trade Exhibi
 tor, Experience Hall Exhibitor\n\n
URL:https://asia.siggraph.org/2023/full-program?id=tog_102&sess=sess209
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