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DTSTAMP:20240214T070244Z
LOCATION:Meeting Room C4.11\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231213T123000
DTEND;TZID=Australia/Melbourne:20231213T124500
UID:siggraphasia_SIGGRAPH Asia 2023_sess169_tog_102@linklings.com
SUMMARY:Digital 3D Smocking Design
DESCRIPTION:Technical Communications, Technical Papers, TOG\n\nJing Ren, A
 viv Segall, and Olga Sorkine-Hornung (ETH Zürich)\n\nWe develop an optimiz
 ation-based method to model smocking, a surface embroidery technique that 
 provides decorative geometric texturing while maintaining stretch properti
 es of the fabric. During smocking, multiple pairs of points on the fabric 
 are stitched together, creating non-manifold geometric features and visual
 ly pleasing textures. Designing smocking patterns is challenging, because 
 the outcome of stitching is unpredictable: the final texture is often reve
 aled only when the whole smocking process is completed, necessitating pain
 staking physical fabrication and time consuming trial-and-error experiment
 ation. This motivates us to seek a digital smocking design method. Straigh
 tforward attempts to compute smocked fabric geometry using surface deforma
 tion or cloth simulation methods fail to produce realistic results, likely
  due to the intricate structure of the designs, the large number of contac
 ts and high-curvature folds. We instead formulate smocking as a graph embe
 dding and shape deformation problem. We extract a coarse graph representin
 g the fabric and the stitching constraints, and then derive the graph stru
 cture of the smocked result. We solve for the 3D embedding of this graph, 
 which in turn reliably guides the deformation of the high-resolution fabri
 c mesh. Our optimization based method is simple, efficient, and flexible, 
 which allows us to build an interactive system for smocking pattern explor
 ation. To demonstrate the accuracy of our method, we compare our results t
 o real fabrications on a large set of smocking patterns.\n\nRegistration C
 ategory: Full Access\n\nSession Chair: Bernd Bickel (Institute of Science 
 and Technology Austria, Google)
URL:https://asia.siggraph.org/2023/full-program?id=tog_102&sess=sess169
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