Quantifying shape similarity of female upper body silhouettes based on 2D images
International Journal of Clothing Science and Technology
ISSN: 0955-6222
Article publication date: 23 October 2023
Issue publication date: 31 October 2023
Abstract
Purpose
This study focused on how to quantify the similarities of body shape based on the front and side images, and a shape comprehensive index (ISC) of female upper body shape based on 2D images was proposed.
Design/methodology/approach
In total, 190 young women were shot for front and side images, and 18 shape parameters were automatically extracted, including seven angles and 11 ratio parameters. The coefficient of variation method was used to assign different weights for related parameters, and the ISC was calculated to describe the body shape of each subject. Five cross-sectional curves of the upper body (e.g. shoulder, chest, waist, abdomen and hip) were selected for exploring the range of shape similarity.
Findings
According to the value of ISC, if the difference among the subjects is within the range of ±0.02, their body shapes can be regarded as similar, and the subject with the minimum distance is considered as the most similar. Error results show that the error range of the angle parameter is from 0.2° to 3.6° and the ratio range is from 0.001 to 0.119. Moreover, the t-test value among the parameters of the similar body is above 0.05, indicating that there is no significant difference for the upper body shape of the similar groups.
Originality/value
This method can quantify body shapes with the upper body characteristics of young women instead of subjective judgment. The study can be extended to other parts of the body and can also provide a new thought for shape similarity retrieval based on 2D images.
Keywords
Acknowledgements
This study was supported by the National Natural Science Foundation of China (Grant No. 61702461), Application and Basic Research Project of China National Textile And Apparel Council (Grant No. J202007), the Fundamental Research Funds of Zhejiang Sci-Tech University (Grant No. 2020Q051), Science and Technology Guiding Project of China National Textile and Apparel Council (Grant No. 2018079) and 2021 National Innovation and Entrepreneurship Training Program for College Students (Grant No. 202110338042).
Since acceptance of this article, the following author have updated their affiliations: Bingfei Gu is at the Clothing Engineering Research Center of Zhejiang Province, Hangzhou, China.
Citation
Xu, K., Zhao, S., Zhang, J. and Gu, B. (2023), "Quantifying shape similarity of female upper body silhouettes based on 2D images", International Journal of Clothing Science and Technology, Vol. 35 No. 6, pp. 986-996. https://doi.org/10.1108/IJCST-10-2022-0137
Publisher
:Emerald Publishing Limited
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