Image-Based Reverse Engineering and Visual Prototyping of Woven Cloth

In: IEEE Transactions on Visualization and Computer Graphics (2014), PP:99
 

Abstract

Realistic visualization of cloth has many applications in computer graphics. An ongoing research problem is how to best represent and capture cloth models, specifically when considering computer aided design of cloth. Previous methods produce highly realistic images, however, they are either difficult to edit or require the measurement of large databases to capture all variations of a cloth sample. We propose a pipeline to reverse engineer cloth and estimate a parametrized cloth model from a single image. We introduce a geometric yarn model, integrating state-of-the-art textile research. We present an automatic analysis approach to estimate yarn paths, yarn widths, their variation and a weave pattern. Several examples demonstrate that we are able to model the appearance of the original cloth sample. Properties derived from the input image give a physically plausible basis that is fully editable using a few intuitive parameters.

Images

Bibtex

@ARTICLE{schroeder_imagebasedcloth_2013,
    author = {Schr{\"o}der, Kai and Zinke, Arno and Klein, Reinhard},
     title = {Image-Based Reverse Engineering and Visual Prototyping of Woven Cloth},
   journal = {IEEE Transactions on Visualization and Computer Graphics},
    volume = {PP},
    number = {99},
      year = {2014},
      note = {To be presented at Pacific Graphics 2014},
  abstract = {Realistic visualization of cloth has many applications in computer graphics. An ongoing research
              problem is how to best represent and capture cloth models, specifically when considering computer
              aided design of cloth. Previous methods produce highly realistic images, however, they are either
              difficult to edit or require the measurement of large databases to capture all variations of a cloth
              sample. We propose a pipeline to reverse engineer cloth and estimate a parametrized cloth model from
              a single image. We introduce a geometric yarn model, integrating state-of-the-art textile research.
              We present an automatic analysis approach to estimate yarn paths, yarn widths, their variation and a
              weave pattern. Several examples demonstrate that we are able to model the appearance of the original
              cloth sample. Properties derived from the input image give a physically plausible basis that is
              fully editable using a few intuitive parameters.},
      issn = {1077-2626},
       doi = {10.1109/TVCG.2014.2339831}
}