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 in | International journal of clothing science and technology Vol. 29; no. 3; pp. 330 - 348 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Bradford
Emerald Publishing Limited
05.06.2017
Emerald Group Publishing Limited |
Subjects | |
Online Access | Get full text |
ISSN | 0955-6222 1758-5953 |
DOI | 10.1108/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. |
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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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Keywords | Point-cloud data Women’s suits Pattern generation Female body feature |
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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... 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... |
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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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