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DTSTAMP:20240214T070240Z
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:Technical Papers\n\nJing Ren, Aviv Segall, and Olga Sorkine-Ho
 rnung (ETH Zürich)\n\nWe develop an optimization-based method to model smo
 cking, a surface embroidery technique that provides decorative geometric t
 exturing while maintaining stretch properties of the fabric. During smocki
 ng, multiple pairs of points on the fabric are stitched together, creating
  non-manifold geometric features and visually pleasing textures. Designing
  smocking patterns is challenging, because the outcome of stitching is unp
 redictable: the final texture is often revealed only when the whole smocki
 ng process is completed, necessitating painstaking physical fabrication an
 d time consuming trial-and-error experimentation. This motivates us to see
 k a digital smocking design method. Straightforward attempts to compute sm
 ocked fabric geometry using surface deformation or cloth simulation method
 s fail to produce realistic results, likely due to the intricate structure
  of the designs, the large number of contacts and high-curvature folds. We
  instead formulate smocking as a graph embedding and shape deformation pro
 blem. We extract a coarse graph representing the fabric and the stitching 
 constraints, and then derive the graph structure of the smocked result. We
  solve for the 3D embedding of this graph, which in turn reliably guides t
 he deformation of the high-resolution fabric mesh. Our optimization based 
 method is simple, efficient, and flexible, which allows us to build an int
 eractive system for smocking pattern exploration. To demonstrate the accur
 acy of our method, we compare our results to real fabrications on a large 
 set of smocking patterns.\n\nRegistration Category: Full Access, Enhanced 
 Access, Trade Exhibitor, Experience Hall Exhibitor
URL:https://asia.siggraph.org/2023/full-program?id=tog_102&sess=sess209
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