• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.73-78
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• 2021

As interest in beauty has increased, various studies have been conducted, and related companies have considered the anthropometric data handled between humans and interfaces as an important factor. However, owing to the nature of 3D human body scanners used to extract anthropometric data, it is difficult to accurately analyze a user's body shape until a service is provided because the user only scans and extracts data. To solve this problem, the body shape of several users was analyzed, and the collected anthropometric data were obtained using a 3D human body scanner. After processing the extracted data and the anthropometric data, a custom deep learning model was designed, the designed model was learned, and the user's body shape information was predicted to provide a service suitable for the body shape. Through this approach, it is expected that the user's body shape information can be predicted using a 3D human body scanner, based upon which a beauty service can be provide.

• Journal of the Korea Fashion and Costume Design Association
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• v.22 no.1
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• pp.1-13
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• 2020

The purpose of this study is to create a 3D avatar from 3D human body shape data using the CLO 3D virtual clothing program and to verify the feasibility of avatar production using the virtual clothing system for verifying size and shape. The research method was to select one virtual representative model that is the closest to the mean size of each body item for each age group. Using the 3D human body scan shape of a 40-69 years old male was applied to the CLO 3D virtual wearing system. Using the CLO 3D Avatar conversion menu, we verified the feasibility of creating a 3D avatar that reproduces the human body scan shape. In the dimension comparison between the 3D avatar and the fictitious representative model, the dimension difference was noticeable in height, circumference, and length. However, as a result, the converted 3D avatar showed less than a 5% difference in most human dimensions. In addition, since the body shape and posture were reproduced similarly, the utilization of the avatar was verified.

• Korean Journal of Computational Design and Engineering
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• v.14 no.6
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• pp.364-373
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• 2009

In this paper, we suggest the method for constructing parameterized human body model which has any required body sizes from 3D scan data. Because of well developed 3D scan technology, we can get more detailed human body model data which allow to generate precise human model. In this field, there are a lot of research is performed with 3D scan data. But previous researches have some limitations to make human body model. They need too much time to perform hole-filling process or calculate parameterization of model. Even more they missed out verification process. To solve these problems, we used several methods. We first choose proper 125 3D scan data from 5th Korean body size survey of Size Korea according to age, height and weight. We also did post process, feature point setting, RBF interpolation and align, to parameterize human model. Then principal component analysis is adapted to the result of post processed data to obtain dominant shape parameters. These steps allow to reduce process time without loss of accuracy. Finally, we compare these results and statistical data of Size Korea to verify our parameterized human model.

• The Research Journal of the Costume Culture
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• v.10 no.6
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• pp.709-717
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• 2002

In the apparel industry, the technology has been advanced rapidly. The use of 3D scanning systems fur the capture and measurement of human body is becoming common place. Three dimensional digital image can be used for design, inspection, reproduction of physical objects. The purpose of this study is to develop a method that drafts men's basic bodice pattern from scanned 3D body surface shape data. In order to pursue this purpose the researchers developed pattern drafting algorithm. The 3D scanner used in this study was Cyberware Whole Body Scanner WB-4. The bodice pattern drafting algorithm from 3D body surface shape data developed in this study is as follows. First, convert geometric 3D body surface data to 3D polygonal mesh data. Second, develop algorithm to lay out 3D polygonal patches onto a plane using Auto Lisp program. The polygon meshes are coplanar, and the individual mesh is continuously in contact with next one The bodice front surface shape data in polygonal patches form was lined up in bust and waist levels. The back bodice was drafted by lining up the polygonal mesh in scapula, chest, and waist levels. in the drafts, gaps between polygons were formed into the darts.

• Journal of Fashion Business
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• v.20 no.2
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• pp.181-196
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• 2016

This study intended to suggest criteria for selection of subjects by lower body shape types necessary for evaluating slacks. For this, the characteristics were examined by lower body parts which would influence the fit of slacks on 3D human body shape data of the front and sides of the lower body for lower body shaping. The frequency of subjects by lower body shape types and the boundary points for discrimination of each type were suggested so that they could be available in selecting subjects. Using the data from Size Korea(2004), indirect measurement values measured on the front and sides of the lower body among 3D human body shape data of 175 subjects were analyzed. Their height, waist, and hip circumference fell under the range of standard deviation based on the mean of women aged 18~24 years, and then lower body shaping was conducted by combining the front and side shapes of the lower body. The front of the lower body was classified into four sections: average waist/average hip type(F1), average waist/narrow hip tyle(F2), narrow waist/narrow hip type(F3) and narrow waist/wide hip type(F4) and the sides of the lower body were divided into four sections: average abdomen/average hip type(S1), flat abdomen/average hip type(S2), average abdomen/protrude hip type(S3)and round abdomen/flat hip type(S4), and thus total 16 lower body types were created by cross analysis. Besides, discriminant analysis suggested the boundary points for each shape type of the front and sides of the lower body as a criterion for deciding lower body shape type of each subject

• Fashion & Textile Research Journal
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• v.17 no.2
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• pp.265-277
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• 2015

The aim of this study was to successfully reflect human body changes on the transformation of the virtual body within 3D virtual fitting spaces. For this purpose, existing problems of shape transformation of the virtual body were analyzed and regression equations which provides useful basic data for transformation of the virtual body that can be applied usefully to the 3D virtual fitting system was developed. Necessary data for the analyses were body measurement and 3D scan data of women with average physical form between the ages of 40 through 49. The reason that we used human body changes of the female subjects in their forties was based on the recognition that fundamental female body changes start to occur from age of forty. Body shapes were largely divided into 3 groups according to obesity which was found to be the biggest factor of shape change. Seven factors were extracted based on factor analysis of 47 body measurement categories and regression equations were created to extract specific measurements for each BMI group based on these seven factors. The major contribution of this paper can be summarized as follows. First, the regression equations to extract specific measurements based on the 7 representative variables remediated existing problem of virtual bodies as it increased the number of body shape transformation areas. Second, the regression equations helped to overcome the problem of current failing to reflecting changes in body cross-section shape based on simple girth measurements based on analysis of cross-section distances.

• Journal of the Korea Computer Graphics Society
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• v.28 no.4
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• pp.1-11
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• 2022

The Skinned Multi-Person Linear Model (SMPL) is the most widely used parametric 3D Human Model optimized and learned from CAESAR, a 3D human scanned database created with measurements from 3,800 people living in United States in the 1990s. We point out the lack of racial diversity of body types in SMPL and propose K-SMPL that better represents Korean 3D body shapes. To this end, we develop a fitting algorithm to estimate 2,773 Korean 3D body shapes from Korean body measurement data. By conducting principle component analysis to the estimated Korean body shapes, we construct K-SMPL model that can generate various Korean body shape in 3D. K-SMPL model allows to improve the fitting accuracy over SMPL with respect to the Korean body measurement data. K-SMPL model can be widely used for avatar generation and human shape fitting for Korean.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.5 s.164
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• pp.692-704
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• 2007

Recently, Basic patterns with excellent body fitness and automation availability are required to be developed in order to automate the patterns of women's clothes. In this study, this reference points, reference lines and segments were fixed onto 3D scan data for the lower body the women in their twenties, they were directly spread out to be 2D flat pattern to facilitate development into the design of slacks adhered closely to the human body such as special and highly-functional clothes, and then slacks 2D pattern was developed for the purpose of seeking scientific approach to the development into basic form slacks and 3d emotional pattern. For conversion of 3D pattern into 2D flat pattern, reference points and segments were created by using Rapid Form of 3D shape analysis software, and triangle mesh of the body surface of the created shape was developed with Auto CAD 2005. The correspondence between slacks and human body was examined by the fixation of major reference lines. Specially, the wearing characteristics of slacks were considered by the fixation of side lines in consideration of posture. As a result of using the way of development to constantly maintain the length while 3D triangle mesh is converted into 2D flat mesh, the shape was shown to be excellently reproduced, and the area of flat pattern was increased compared to the shape of parting plane. Also, the sunk-in curve like the brief line of front crotch length needed a cutting line when it was closely adhered, when mesh was overlapped, and the pattern area was smaller compared to the actual shape.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.3
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• pp.440-458
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• 2019

Based on a 3D body data and pattern comparison analysis, this study developed a formal jacket pattern for men in their late 30s. In order to select the representative type of men in their late 30s, factor analysis and cluster analysis were conducted on data form 319 men, 35 to 39 years old using the anthropometric data from The 7th Size Korea (2015) as the representative body type. The surface of the body surface was developed using a 3D human shape of a male in his 30s in The 6th Size Korea (2010). Then the shape was changed to a flat pattern that confirmed the necessary elements for setting the shape and dimension. Cluster analysis revealed type B as the representative type because it showed the best shape characteristics for men in the late 30s. The drafting method of the final research pattern is as follows. Jacket length: stature/2.5cm, back length: stature/5+8.5cm (constant)], armhole depth: [stature/ 7-1.5cm (constant)], back width: [C/9+9.5cm (constant)]+1cm (ease), front width: [C/9+8.5cm (constant)]+1cm (ease), armscye depth: C/8, front waist darts: 1cm, front closure amount: 2cm.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.4
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• pp.147-161
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• 2023

This study used 3D anthropometric data from the 8th Size Korea to type and analyze whole body shapes of obese women in their 20s and 30s, and constructed dimensional data for human body items needed to create a 3D human body model for each type. The data analysis used data from 148 obese women in their 20s and 30s, and a total of 48 index values, drop values, and angle items were subjected to factor analysis and one-way variance analysis to categorize body types and verify significant differences by type. As a result of the factor analysis, 12 factors were extracted and divided into 4 body types. Type 1 is a 'standard type with a curved torso with balanced upper and lower body lengths', Type 2 is a 'bending forward type with a short, thick lower body, and an uncurved torso', Type 3 is a 'lean back type with a long and thin lower body and an H-shape torso', Type 4 is a 'sway back type with a long and thick lower body and abdominal obesity'. The representative body type of obese women in their 20s and 30s was identified as Type 1. The constructed body shape information will be used as basic data for future 3D human body modeling.