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Wrinkling Captured Garments Using Space-Time Data-Driven Deformation.

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Title: Wrinkling Captured Garments Using Space-Time Data-Driven Deformation.
Authors: Popa, T.1, Zhou, Q.1, Bradley, D.1, Kraevoy, V.1, Fu, H.1,2, Sheffer, A.1, Heidrich, W.1
Source: Computer Graphics Forum. Apr2009, Vol. 28 Issue 2, p427-435. 9p. 1 Color Photograph, 8 Diagrams, 1 Chart.
Subjects: Clothing & dress, Digital image processing software, Computer-aided imagery software, Computer graphics research, Computer graphics software, Three-dimensional imaging, Computer software
Abstract: The presence of characteristic fine folds is important for modeling realistic looking virtual garments. While recent garment capture techniques are quite successful at capturing the low-frequency garment shape and motion over time, they often fail to capture the numerous high-frequency folds, reducing the realism of the reconstructed space-time models. In our work we propose a method for reintroducing fine folds into the captured models using data-driven dynamic wrinkling. We first estimate the shape and position of folds based on the original video footage used for capture and then wrinkle the surface based on those estimates using space-time deformation. Both steps utilize the unique geometric characteristics of garments in general, and garment folds specifically, to facilitate the modeling of believable folds. We demonstrate the effectiveness of our wrinkling method on a variety of garments that have been captured using several recent techniques. [ABSTRACT FROM AUTHOR]
Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: <searchLink fieldCode="DE" term="%22Clothing+%26+dress%22">Clothing & dress</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+image+processing+software%22">Digital image processing software</searchLink><br /><searchLink fieldCode="DE" term="%22Computer-aided+imagery+software%22">Computer-aided imagery software</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+graphics+research%22">Computer graphics research</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+graphics+software%22">Computer graphics software</searchLink><br /><searchLink fieldCode="DE" term="%22Three-dimensional+imaging%22">Three-dimensional imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software%22">Computer software</searchLink>
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  Data: The presence of characteristic fine folds is important for modeling realistic looking virtual garments. While recent garment capture techniques are quite successful at capturing the low-frequency garment shape and motion over time, they often fail to capture the numerous high-frequency folds, reducing the realism of the reconstructed space-time models. In our work we propose a method for reintroducing fine folds into the captured models using data-driven dynamic wrinkling. We first estimate the shape and position of folds based on the original video footage used for capture and then wrinkle the surface based on those estimates using space-time deformation. Both steps utilize the unique geometric characteristics of garments in general, and garment folds specifically, to facilitate the modeling of believable folds. We demonstrate the effectiveness of our wrinkling method on a variety of garments that have been captured using several recent techniques. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/j.1467-8659.2009.01382.x
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              Text: Apr2009
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