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.
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.
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.
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.
This work is supported by Science Foundation of Zhejiang Sci-Tech University (ZSTU) under Grand No. 16072195-Y, and the Natural Science Foundation of Jiangsu Province under Grand No. BK20151191.
Gu, B., Gu, P. and Liu, G. (2017), "Pattern generation rules for basic women’s suits", International Journal of Clothing Science and Technology, Vol. 29 No. 3, pp. 330-348. https://doi.org/10.1108/IJCST-06-2016-0066
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