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research article

Structure-aware Synthesis for Predictive Woven Fabric Appearance

Zhao, Shuang
•
Jakob, Wenzel  
•
Marschner, Steve
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2012
ACM Transactions on Graphics

Woven fabrics have a wide range of appearance determined by their small-scale 3D structure. Accurately modeling this structural detail can produce highly realistic renderings of fabrics and is critical for predictive rendering of fabric appearance. But building these yarnlevel volumetric models is challenging. Procedural techniques are manually intensive, and fail to capture the naturally arising irregularities which contribute significantly to the overall appearance of cloth. Techniques that acquire the detailed 3D structure of real fabric samples are constrained only to model the scanned samples and cannot represent different fabric designs. This paper presents a new approach to creating volumetric models of woven cloth, which starts with user-specified fabric designs and produces models that correctly capture the yarn-level structural details of cloth. We create a small database of volumetric exemplars by scanning fabric samples with simple weave structures. To build an output model, our method synthesizes a new volume by copying data from the exemplars at each yarn crossing to match a weave pattern that specifies the desired output structure. Our results demonstrate that our approach generalizes well to complex designs and can produce highly realistic results at both large and small scales. © 2012 ACM 0730-0301/2012/08-ART75.

  • Details
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Type
research article
DOI
10.1145/2185520.2185571
Author(s)
Zhao, Shuang
•
Jakob, Wenzel  
•
Marschner, Steve
•
Bala, Kavita
Date Issued

2012

Publisher

ACM

Published in
ACM Transactions on Graphics
Volume

31

Issue

4

Start page

75:1

End page

75:10

Subjects

appearance modeling

•

textiles

•

volume rendering

Peer reviewed

REVIEWED

Written at

OTHER

EPFL units
RGL  
Available on Infoscience
July 25, 2016
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/128103
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