• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.4
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• pp.165-179
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• 2019

This study used 3D body scan data to classify body shapes according to the torso shape of adult males aged 20-75 years. This data will be provided so that the apparel industry can make apparel products corresponding to body characteristics by age. The study used 1,796 adult males between the ages of 20 and 75 and the 3D body shape data of the '5th Research on National Standard Anthropometry'. For data analysis, the program SPSSWIN Ver. 17.0 was used to calculate the mean and frequency allowing for a factor analysis, cluster analysis, analysis of variance, and Duncan test. To classify body shape according to the torso shape of adult males, this study considered nine factors: 'horizontal size of torso,' 'vertical size of body,' 'curve of torso and waist-abdomen flatness ratio,' 'length of torso,' 'shape of neck area,' 'degree of lateral curve,' 'difference between front and back interscye length,' 'shoulder armscye shape,' and 'chest flatness ratio.' Based on the results of the factor analysis, the torso shapes of adult males were classified into five types. Type 1 is "upright body with flat, curvy shape", Type 2 is "curve sway back body type", Type 3 is "flat, abdominally obese body", Type 4 is "obese, crooked body" and Type 5 is "thick sway front body type." named.

• 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.

• 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 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.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.3
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• pp.511-530
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• 2023

This study aims to analyze middle-aged men's frontal body shape asymmetry by measuring the left and right body dimensions and angles of 388 middle-aged men aged 40 to 59 using 3D body scan data and comparing the measured values. The study also compares the measured values of width, height, and angle and their relationships using Size Korea's anthropometric measurement and posture index of the New York Posture Rating Scale. The results confirm that the asymmetric shape characteristics of the upper and lower body appear differently. In addition, the asymmetrical characteristics between the upper and lower body differed, indicating that the close parts of the body affect each other. Similar to the difference in the left and right frontal body shapes and the average angle distribution, the asymmetrical upper and lower body characteristics also are found to be dissimilar when the correlations are examined. In contrast, there is no asymmetry in the width, height, and angle considering the age and BMI groups. Finally, the study classifies three body types and identifies their asymmetric characteristics. Overall, this study contributes primary data for further research on pattern production for asymmetric and unique body types and the development of customized apparel products.

• International Journal of Human Ecology
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• v.15 no.2
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• pp.13-21
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• 2014

This study investigated the anthropometric characteristics of US women 26 to 45 years of age to classify their body shapes into different categories. Research data was obtained from 2950 women 26 to 45 years of age who participated in the SizeUSA study. A 26 to 35 years of age group and a 36 to 45 years of age group were selected from the data pool. A total of 26 measurements important for body shape classification and for apparel product development was used for the data analysis. Five factors accounted for the US women's body measurements. The body shapes of women were categorized into 4 types: Obese A-Shape, Overweight Y-Shape, Obese H-Shape, and Normal S-Shape. Normal S-Shape was the most common body shape type. More women in the 26 to 35 years of age group had Normal S-Shape type than women in the 36 to 45 years of age group. More women in the 36 to 45 years of age group had Obese A-Shape, Overweight Y-Shape, and Obese H-Shape than women in the 26 to 35 years of age group. Younger US women, 26 to 35 years of age had slimmer body sizes with more balanced body shapes; however, older US women, 36 to 45 years of age had larger body sizes with more various body shapes.

• 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 Fashion Business
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• v.22 no.3
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• pp.122-142
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• 2018

In the virtual fitting system, the use of a 3D avatar is not a simple garment model, but it should be able to reproduce the size and shape of the customer using a fitting system. Although various virtual fitting systems have their own 3D avatar sizing systems and provide 3D avatars that match the size of the customer, there are limitations in realizing the actual body shape in actual use by the consumer. The purpose of this study is to realize a 3D avatar with excellent size and conformity for customer use. Therefore, this study aims to provide basic data for the formation of a 3D standard avatar of Korean women aged in their 20's, by comparing and analyzing the degree of the consumer user friendly system change of a body type, and the consumer's ability in selecting a consumer representative body type. Based on the survey data of 'Size Korea' conducted from 2004 to 2015 at three times, we examined the change of body shape over 10 years. Then, based on the results of 6th and 7th data, 4 factors of the concurrent body shape change of women of the consumer demographic studied were selected through the use of a factor analysis. Following this analysis, the 4 extracted factors were clustered again and finally released 7 representative body types, which were obtained based on height and weight. The size of each representative figure is derived by the use of a regression analysis, and it is used as a basic data for 3D avatar formation of the virtual fitting system.

• The Research Journal of the Costume Culture
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• v.17 no.6
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• pp.1099-1111
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• 2009

The purpose of this study is to classify body shapes of aged women by using 3D body scan data. For the body shape analysis and classification, 3D body scan data of 270 aged women were used, and 16 main measurements consisting of a human body were used to conduct factor analysis, cluster analysis and discriminant analysis. The analysis were performed on all 'the method using the absolute value', 'the method using index of height and weight', and 'the method using index of height', and according to the classification results, the method which categorizes body shapes best in terms of their shapes was adopted. As the factor analysis result using the numerical value of height to categorize the body shapes of the aged women, factor 1 was the thickness and width for the height, factor 2 was the height of the upper part of the body for the height, factor 3 was the height of hips for the height, and factor 4 was the height of belly for the height. When the body shapes were categorized with the deducted factors as variables, they were divided into two types. Type 1 was a short and fat body shape($\blacksquare$ type) and 55.6% of the subjects were of this type. Type 2 was for the body shape whose vertical height, including weight, was long but all kinds of width and thickness were small, that is, tall and thin body shape($\blacksquare$ type), and 44.4% of the aged women were in this case.