Study on Pattern Design Method of Women Tight Skirts Based on 3D Point-cloud Data
DOI:
10.3993/jfbi03201208
Journal of Fiber Bioengineering & Informatics, 5 (2012), pp. 85-93.
Published online: 2012-05
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@Article{JFBI-5-85,
author = {Pingying Gu, Qian Qian, Ting Chen, Lei Huang, Haiyan Kong and Guolian Liu},
title = {Study on Pattern Design Method of Women Tight Skirts Based on 3D Point-cloud Data},
journal = {Journal of Fiber Bioengineering and Informatics},
year = {2012},
volume = {5},
number = {1},
pages = {85--93},
abstract = {In this research, 100 female students aged from 18 to 24 years old were selected to take part in the
body measurement. Data acquisition software named Imageware with a 3D scanner was employed to
gain the body point-cloud diagram. Then, the characteristics of the young female lower body torso have
been analyzed according to the data obtained. The regression of the key parts of women skirts and the
characteristics of young female lower body torso has been found. Finally, the generating rules of the
basic pattern of women skirts were established, which provides the foundation for auto-generation of
skirt pattern.},
issn = {2617-8699},
doi = {https://doi.org/10.3993/jfbi03201208},
url = {http://global-sci.org/intro/article_detail/jfbi/4864.html}
}
TY - JOUR
T1 - Study on Pattern Design Method of Women Tight Skirts Based on 3D Point-cloud Data
AU - Pingying Gu, Qian Qian, Ting Chen, Lei Huang, Haiyan Kong & Guolian Liu
JO - Journal of Fiber Bioengineering and Informatics
VL - 1
SP - 85
EP - 93
PY - 2012
DA - 2012/05
SN - 5
DO - http://doi.org/10.3993/jfbi03201208
UR - https://global-sci.org/intro/article_detail/jfbi/4864.html
KW - 3D Body Measurement
KW - Women Skirts
KW - Pattern Auto-generation
KW - Imageware
AB - In this research, 100 female students aged from 18 to 24 years old were selected to take part in the
body measurement. Data acquisition software named Imageware with a 3D scanner was employed to
gain the body point-cloud diagram. Then, the characteristics of the young female lower body torso have
been analyzed according to the data obtained. The regression of the key parts of women skirts and the
characteristics of young female lower body torso has been found. Finally, the generating rules of the
basic pattern of women skirts were established, which provides the foundation for auto-generation of
skirt pattern.
Pingying Gu, Qian Qian, Ting Chen, Lei Huang, Haiyan Kong and Guolian Liu. (2012). Study on Pattern Design Method of Women Tight Skirts Based on 3D Point-cloud Data.
Journal of Fiber Bioengineering and Informatics. 5 (1).
85-93.
doi:10.3993/jfbi03201208
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