Abstract
Clothing pressure is an important factor that influences wear comfort. It can reflect wear comfort intuitively. With the development of virtual-reality technology, the numerical clothing pressures were widely applied in the evaluations of garment wear comfort. Compared with traditional measuring methods of garment pressure, the virtual clothing pressure-measuring method has the advantages of lower cost, time saving, efficiency improving, easy accessibility, and higher accuracy. In this article, sixty human’s postures in daily life were designed using CLO 3D Modelist. Next, the numerical clothing pressure data were collected, respectively, under the sixty postures in a virtual environment. Finally, factor analysis was applied to process the data. The result shows that the pants’ pressure wear comfort is mainly influenced by four factors; there are thigh–hip factor, shank factor, waist factor, and crotch factor. The share of these four factors’ influence accounts for about 82.0%, and the thigh–hip factor takes up the biggest share and reaches to 44.5%.
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This paper was financially supported by China National Endowment for the Arts.
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Liu, K. (2018). Garment Wearing Comfort Analysis Using Data Mining Technology. In: Thomassey, S., Zeng, X. (eds) Artificial Intelligence for Fashion Industry in the Big Data Era. Springer Series in Fashion Business. Springer, Singapore. https://doi.org/10.1007/978-981-13-0080-6_13
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