Pattern generation rules for basic women’s suits

Purpose The purpose of this paper is to focus on how to automatically generate the individualized patterns for women’s suits based on the 3D body point-cloud images. Design/methodology/approach With the software Imageware, the point-cloud data of the female body were measured according to the female...

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Published inInternational journal of clothing science and technology Vol. 29; no. 3; pp. 330 - 348
Main Authors Gu, Bingfei, Gu, Pinying, Liu, Guolian
Format Journal Article
LanguageEnglish
Published Bradford Emerald Publishing Limited 05.06.2017
Emerald Group Publishing Limited
Subjects
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ISSN0955-6222
1758-5953
DOI10.1108/IJCST-06-2016-0066

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Abstract Purpose The purpose of this paper is to focus on how to automatically generate the individualized patterns for women’s suits based on the 3D body point-cloud images. Design/methodology/approach With the software Imageware, the point-cloud data of the female body were measured according to the female body feature to obtain the heights, widths, depths and girths at various landmarks. Then the relationship between the height of each landmark and the body height was analyzed to build the height calculation rules by software SPSS, and the prediction models of body girths were established from the body widths and depths using regression analysis for pattern generation. Findings The pattern generation rules were built with the relationships between a human body and the garment patterns using the graphic flattening method. Based on the above rules, the final patterns were drafted automatically by using these dimensions to fit the subjects. The try-on experiment also showed that the individualized suits could fit the subjects’ body well at some feature landmarks. Originality/value In order to realize tailor-made and meet the consumers’ demands for individualized clothes, the development of garment CAD system has become inevitable in the garment industry. This paper could provide the foundation for automatic pattern generation, and technical support for tailor-made.
AbstractList Purpose The purpose of this paper is to focus on how to automatically generate the individualized patterns for women’s suits based on the 3D body point-cloud images. Design/methodology/approach With the software Imageware, the point-cloud data of the female body were measured according to the female body feature to obtain the heights, widths, depths and girths at various landmarks. Then the relationship between the height of each landmark and the body height was analyzed to build the height calculation rules by software SPSS, and the prediction models of body girths were established from the body widths and depths using regression analysis for pattern generation. Findings The pattern generation rules were built with the relationships between a human body and the garment patterns using the graphic flattening method. Based on the above rules, the final patterns were drafted automatically by using these dimensions to fit the subjects. The try-on experiment also showed that the individualized suits could fit the subjects’ body well at some feature landmarks. Originality/value In order to realize tailor-made and meet the consumers’ demands for individualized clothes, the development of garment CAD system has become inevitable in the garment industry. This paper could provide the foundation for automatic pattern generation, and technical support for tailor-made.
PurposeThe purpose of this paper is to focus on how to automatically generate the individualized patterns for women’s suits based on the 3D body point-cloud images.Design/methodology/approachWith the software Imageware, the point-cloud data of the female body were measured according to the female body feature to obtain the heights, widths, depths and girths at various landmarks. Then the relationship between the height of each landmark and the body height was analyzed to build the height calculation rules by software SPSS, and the prediction models of body girths were established from the body widths and depths using regression analysis for pattern generation.FindingsThe pattern generation rules were built with the relationships between a human body and the garment patterns using the graphic flattening method. Based on the above rules, the final patterns were drafted automatically by using these dimensions to fit the subjects. The try-on experiment also showed that the individualized suits could fit the subjects’ body well at some feature landmarks.Originality/valueIn order to realize tailor-made and meet the consumers’ demands for individualized clothes, the development of garment CAD system has become inevitable in the garment industry. This paper could provide the foundation for automatic pattern generation, and technical support for tailor-made.
Author Gu, Pinying
Gu, Bingfei
Liu, Guolian
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10.1016/j.compind.2010.03.004
10.5997/sposun.3.19
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10.1108/13612021111169915
10.1016/j.compind.2012.04.001
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Keywords Point-cloud data
Women’s suits
Pattern generation
Female body feature
Language English
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SubjectTerms Body measurements
Females
Human body
Landmarks
Neural networks
Pattern analysis
Pattern generation
Regression analysis
Software
Technical services
Three dimensional bodies
Three dimensional models
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Title Pattern generation rules for basic women’s suits
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