Estimating Garment Patterns from Static Scan Data

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The acquisition of highly detailed static 3D scan data for people in clothing is becoming widely available. Since 3D scan data is given as a single mesh without semantic separation, in order to animate the data, it is necessary to model shape and deformation behaviour of individual body and garment parts. This paper presents a new method for generating simulation-ready garment models from 3D static scan data of clothed humans. A key contribution of our method is a novel approach to segmenting garments by finding optimal boundaries between the skin and garment. Our boundary-based garment segmentation method allows for stable and smooth separation of garments by using an implicit representation of the boundary and its optimization strategy. In addition, we present a novel framework to construct a 2D pattern from the segmented garment and place it around the body for a draping simulation. The effectiveness of our method is validated by generating garment patterns for a number of scan data.
Publisher
WILEY
Issue Date
2021-09
Language
English
Article Type
Article
Citation

COMPUTER GRAPHICS FORUM, v.40, no.6, pp.273 - 287

ISSN
0167-7055
DOI
10.1111/cgf.14272
URI
http://hdl.handle.net/10203/288035
Appears in Collection
GCT-Journal Papers(저널논문)
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