• DocumentCode
    1763657
  • Title

    Image-Based Reverse Engineering and Visual Prototyping of Woven Cloth

  • Author

    Schroder, Kai ; Zinke, Arno ; Klein, Reinhard

  • Author_Institution
    Inst. of Compute Sci. 2, Univ. of Bonn, Bonn, Germany
  • Volume
    21
  • Issue
    2
  • fYear
    2015
  • fDate
    Feb. 1 2015
  • Firstpage
    188
  • Lastpage
    200
  • 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.
  • Keywords
    CAD; clothing; data visualisation; production engineering computing; reverse engineering; weaving; woven composites; yarn; cloth computer aided design; cloth visualization; computer graphics; geometric yarn model; image-based reverse engineering; parametrized cloth model; weave pattern; woven cloth visual prototyping; Computational modeling; Image segmentation; Optical imaging; Visualization; Weaving; Yarn; BCSDF; CAD; Optical material properties; cloth; cloth analysis; cloth model; computer graphics; design; fibers; reverse engineering; weave pattern; yarn model;
  • fLanguage
    English
  • Journal_Title
    Visualization and Computer Graphics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1077-2626
  • Type

    jour

  • DOI
    10.1109/TVCG.2014.2339831
  • Filename
    6858070