• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.4
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• pp.107-122
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• 2023

This study analyzed the style, dimensions, fabric patterns, colors, and fabrics of a traditional Chinese women's dress from the Zhou Dynasty, and reconstructed it in the form of a virtual garment using 3D CLO. Based on ancient flat image data and three-dimensional portrait data, who wore them, how they were worn, and how they were coordinated was analyzed. In order to analyze the size and pattern of the straight Ju Chines dress, data from the excavation report and the tomb owner's anthropometric measurements were combined to infer the wearing condition and organize the sculptural features. Dimensional analysis was carried out using a well-preserved small-scale woven cotton cloth as a restoration model, and the horizontal and vertical dimensions were reasonably estimated using the shape proportioning method. The analysis of the colors and patterns of the fabrics was based on the colors and patterns of the fabrics excavated from Masan Tomb No. 1 during the Eastern Zhou, Qin, and Han periods. Finally, a virtual model was created using data from the excavation report and the age and height information of the owner of the excavated robe, and the pose and size of the virtual model were determined using 3D CLO. Based on the previous research data, the garment was virtually sewn and simulated. The shape, pressure, and strain of the garment in different postures was also compared. Through the research direction of pattern and 3D restoration, this research maximizes the restoration of Chinese traditional women's dress and presents it in a more intuitive, comprehensive, and vivid way.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.117-125
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• 2023

In the development of clothing design through virtual simulation, it is essential to minimize the differences between the virtual and the real world as much as possible. The most critical task to enhance the similarity between virtual and real garments is to find simulation parameters that can closely emulate the physical properties of the actual fabric in use. The simulation parameter optimization process requires manual tuning by experts, demanding high expertise and a significant amount of time. Especially, considerable time is consumed in repeatedly running simulations to check the results of applying the tuned simulation parameters. Recently, to tackle this issue, artificial neural network learning models have been proposed that swiftly estimate the results of drape test simulations, which are predominantly used for parameter tuning. In these earlier studies, relatively simple linear stiffness models were used, and instead of estimating the entirety of the drape mesh, they estimated only a portion of the mesh and interpolated the rest. However, there is still a scarcity of research on non-linear stiffness models, which are commonly used in actual garment design. In this paper, we propose a learning model for estimating the results of drape simulations for non-linear stiffness models. Our learning model estimates the full high-resolution mesh model of drape. To validate the performance of the proposed method, experiments were conducted using three different drape test methods, demonstrating high accuracy in estimation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.103-107
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• 2009

Because individual HRTFs (Head-Related Transfer Functions) vary from a person to a person, a HRTF database has been measured by researchers to investigate the inter-subject variation, and to generate high fidelity virtual sound image. Individual HRTFs not only vary between subjects but also vary due to wearing clothes and glasses in daily life. However, influence of different dressing condition on the measured HRTF was not sufficiently investigated. To quantify the effect of wearing clothes and glasses, dummy's HRTF is measured in an anechoic chamber with various dressing condition, and is evaluated in the sense of spectral distortion. HRTFs are measured both in the median plane and in the horizontal plane. In the median plane, under 6kHz, effect of different wearing clothes and glasses is negligible. Over 6kHz, however, effect of clothing distorts HRTF about 6dB in the sense of spectral distortion. Moreover, at high frequencies, effect of glasses is no longer negligible. In the horizontal plane, at some azimuths, even additional light cloth over the dummy can change the spectrum of HRTF (6dB spectral distortion) especially when sound source is at contralateral positions. Therefore, HRTF measurement with different wearing conditions can broaden the capability of HRTF customization whose technique utilizes a HRTF database.

• Journal of Fashion Business
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• v.13 no.1
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• pp.102-114
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• 2009

Chitosan is a polysaccharide with cationic amino groups in its structure and has useful properties as functional materials. Various end-use developments of chitosan are in progress. When the cotton fabric is pretreated with chitosan, the hand property of cotton fabric may be improved expecially for the summer apparel. In this study, as a cross-linking agent to introduce chitosan into cotton, BTCA(butane-1,2,3,4-tetracarboxylic acid) or CA(citric acid) was added in order to prevent detachment of chitosan by the cross-linking. During the cross-linking procedure, via the padding-drying-heat setting, amino groups of chitosan and hydroxyl groups of cotton, carboxyl groups of BTCA/CA are cross-linked by forming anhydrous cyclic rings. Since BTCA has four carboxyl groups, cross-linking by thermal treatment is easy, leading to the trials in wrinkle-recovery treatment of cotton fabrics. However, the high price of the BTCA reagent has been a shortcoming in the actual application for industrial use. Therefore, in this study, we tried the application of CA having three carboxyl groups, which is relatively low priced, as the substituting cross-linking agent. The hand of the treated fabrics were evaluated by measuring physical properties. In addition, based on the physical properties, three-dimensional images were introduced by using 3D CAD systems and results were compared.