Stationary 3D whole-body scanners generally require 5 to 20 seconds of scanning time and cannot effectively detect armpit and crotch areas. Therefore, this study aimed to analyze the accuracy of a photogrammetric technique using a multi-camera system. First, dimensional accuracy was analyzed using a mannequin scan, comparing the differences between the scan-derived measurements and the direct measurements, with an allowable tolerance of ISO 20685-1:2018. Only 2 of 59 measurement items (ankle height and upper arm circumference, specifically) exceeded the ISO 20685-1:2018 criteria. When compared with the results of the eight stationary whole-body scanners assessed by the literature, the photogrammetric technique was found to have the advantage of scanning the top of the head, armpit, and crotch areas clearly. Second, this study found the photogrammetric technique is suitable for obtaining the body scans because it can minimize the perform scanning, resulting in a reduction of measurement errors due to breathing and uncontrolled movements. The error rate of the photogrammetry method was much lower than that of stationary 3D whole-body scanners.
This study analyzed differences between three-dimensional (3D) body scanning and manual measurements, aiming to assess whether 3D scanning can replace traditional anthropometric tools, such as tape measures and calipers. Data from 4,478 participants in the 8th Size Korea Project were analyzed, covering 43 measurement items. Since Given that the 3D and manual measurements were performed on the same subjects in the 8th Size Korea Project, it was possible to determine the correlation more accurately between the two measurement methods more accurately. Using Applying ISO 20685-1(2018) standards, 15 out of the 43 items fell within allowable error limits. When classified into six types, "small circumferences" and "segment lengths" showed averages of 3.35 mm and 3.10 mm, respectively, within acceptable range. "Body heights" and "body depths" slightly exceeded the limit, with averages of 5.28 mm and 6.58 mm. "Body widths" and "large circumferences" surpassed the limit, with means of 16.77 mm and 16.18 mm. The study offers an objective basis to for validate validating 3D measurements' measurements' reliability and accuracy, addressing various industries' needs for information on the human body's dimensions information.
Somatotype is human body shape and physique type which can be classified not only by the size, but also by the shape or posture of the body. Postural variations in the alignment of the back, shoulder, and neck can have an adverse effect on the fit of garments designed to hang from the shoulders. There have been some previous studies about the lateral upper torso by analyzing photographic measurements. In this study, 3D body scan images were used to classify the side somatotype of upper lateral method even though they are major data in the classification of upper torso. This study focused on following objective.; 1) To apply new and developing technology into the apparel industry analyzing 3D body scan images. 2) To classify upper laterla torso using the data through the new improver technology, 3D body scanner. 3) To propose basic materials for well fitted garments for each type of figure. The test subjects for this study were two hundreds nine female aged 19 years and up who were recruited in Cornell university body scan research team. Seventeen Variables(12 angles, 5 lengths) out of 3D body scan data were measured based on these landmarks and applied to analyze. The result of factor analysis indicated that 6 factors were extracted through factor analysis and orthogonal rotation by the method of Varimax and those factors comprise 62.5% of total variance. And the somatotype of upper body is classified into 3 types of figures according to cluster analysis; Bent forward posture, Straight posture, Swayback posture. Future study could be addressed about the somatotype of body by the age group based on the large database with wide variety of age.
This research is to understand customer satisfaction with virtual fitting based on a 3D body scanner and avatars as well as differences between avatars and the 'real me'. To this end, this research examined Korean college students to facilitate 3D body scanning, avatar generation and surveys. The author used 3D body scan data with direct measurements to identify differences between the 3D body scan data-based 'my avatar' and 'real me' in the virtual dress fitting system. The survey results on 'the level of customer awareness on 3D body scanner' found that the majority of both genders did not know about it and indicated a lower usability to incorporate IT technology into the fashion industry. The question in the 3D body scanning and avatar found an affirmative attitude. Satisfaction levels on the 3D avatars' similarity with 'own body' and garment fitting were positive and indicated a need for further technological improvements to express the avatars identical to customers' own body. More research is necessary for the accuracy of sizes for 3D body scanning that measure body sizes while wearing clothes. Avatars based on such datamay be less similar to 'own body' and cause customer dissatisfaction. Thus, further technology development is required to narrow gaps using data to make avatars that provide more accurate virtual fitting simulation services to customers.
The most researches developing pattern of compression style sportswear were targeted at the live model that has muscular body build. The purpose of this study was developing a method for classifying men's lower body types in terms of muscular body build. The 3D human body scan data and body measurements of 30s of Size Korea were analyzed. The subjects (n=203) were men between the ages of 30 and 39 years. Men's muscular body build was classified with two key dimensions, thigh girth and calf girth. The subjects were divided into four groups. From each group, average subjects (n=42) whose height and weight were close to the mean value ($mean{\pm}1/2$ S.D.) were selected. 42 subjects were divided up as four groups. Group I (n=7) was thigh and calf developed body type. Group II (n=9) was thigh developed body type. Group III (n=11) was calf developed body type. Group IV (n=15) was thigh and calf undeveloped body type. Four groups had distinct different at widths (n=4), depths (n=4), and girths (n=9) dimensions. The results showed that the muscular men in their 30s could be defined by thigh and calf girths. The thigh developed muscular men had thigh girth over 60cm and the calf developed muscular men had calf girth over 38cm. From each group one representative was selected by 3D body scan figure.
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.
The purpose of this study is to provide basic information for the development of pants patterns with a high level of fit and comfort through calculating surface variations of lower body parts by movement, grouping them into factors, and analyzing how their surface variations link to one another. The achieved results will help determine essential elements for constructing pants patterns, such as key measurements of lower body parts, the amount of ease values and selection of fabrics, which should be taken into consideration for allowing better movement in clothing. The study required lower body 3D scanning of women for analysis, and 13 women between the ages of 20-24 participated in the scanning, which was done by using Artec Eva 3D scanner. Their scanned data were digitalized and converted to measure the values of their lower body surface length and girth in pre-determined positions such as walking, stair climbing and sitting on a chair. These measurements have been statistically analyzed through SPSS 21.0 to obtain the average amounts and rates of extension for each of the measurement item. Some of the highlighted study results are as follows: The surface length and girth measurements were grouped into 4 factors based on their average extension rates. The results from correlation analysis between measurement items within each factor demonstrated that common items linked to all the changes in the values of other items in the three movements. But in most cases, items were not always correlated with each other for different movements. The results also showed that there were correlations between girth measurements, length measurements, and girth and length measurements. Therefore, key measurements for daily pants should be determined within reasonable estimations between relevant measurement items, while the measurements for work pants, which often withstand certain postures or repetitive movements, may require measurement items that are appro priate for, and closely related to, certain movements or tasks.
This study was designed to propose a method to draft bodice block pattern from 3D body scan data. Subjects were ten elderly women in their 60's, who wear basic size(B: 94cm, W: 82cm) garment. Scanning was done using 3D whole body scanner(WB4, Cyberware). Measurements for 3D data and cross section were attained using Auto CAD, by which a upper bodice pattern for elderly women was drawn on the basis of short measured method. The results are as following: As for most items, no significant differences were shown between measurements from Martin's anthropometry and those from 3D scan data, suggesting measurement from 3D scan data could be used to draft a pattern. The drafting equations acquired were as follows; width of pattern=B/2+5.5, width of waist=W/2+3.5cm, dart amount=8cm. Dart distributions were 23%(B.P.) : 20%(front armpit) : 17%(side seam) : 18%(back armpit) : 15%(back protruded point) : 7% (center back line). Through wearing test using 5-point Likert scale, resultant pattern was evaluated as appropriate for elderly women's pattern to get over 4 point. As a result, it might be said that 3D scanning application is effective for elderly women in that it doesn't take time so much as Martin's anthropometry and that their body shape vary compared with those of young women.
This study aims to design a new sizing system for hygienic masks to protect against COVID-19-related respiratory disorders. The product sizes were collected from 70 commercially available hygienic masks, and 18 head measurements were obtained from the three-dimensional (3D) scan data of 2,048 men and women aged 20 to 69 years from the 6th Size Korea Survey. The statistical analysis was performed using the IBM Statistical Package for the Social Sciences (SPSS) 28.0 program. The "bitragion-subnasale arc" and "menton-sellion length" were chosen as the key body dimensions for the hygienic mask sizing system. The linear regressions with 18 3D head measurements were analyzed, and it was determined that the key body dimensions were useful for statistically predicting other 3D head measurements related to hygienic masks. A new sizing system was proposed for two types of masks, "masks with a tight fit" and "masks with a loose fit," taking into account the existing Korean Industrial Standards (KS) and the shortcomings of the sizes of hygienic masks on the market. The sizing system for tight-fitting masks consisted of the key body dimensions, with their sizes indicated by a pair of numbers. The sizing system for loose-fitting masks consisted solely of the bitragion-subnasale arc, with their sizes denoted by letters such as S, M, and L (denoting small, medium, and large, respectively). Future studies should consider this mask sizing system for different age groups, such as children and adolescents.
Two hundreds of female aged 19 years old and up were recruited to evaluate the postural changes and bilateral variation of asymmetry over age. To find out the differences among the age group, subjects were classified into 5 groups, early young age(19-29), late young age(30-39), early middle age(40-49), late middle age(50-59), and old age(60-). 35 body measurements were taken by the 3-D body scanner which allowed us to take measurements which cannot be measured using traditional methods, including the shape of a cross section, slice area surface are, and volume. Bilateral variations were observed as a function of age; Depth of scapular point level, scapular point to center back, and blade angle. Postural change of anterior cervical angle, upper anterior thoracic angle, upper posterior thoracic angle, posterior cervical angle, and center back/center front ratio were also exhibited. In each measurements, subjects were classified into normal, and abnormal group. Percentiles of abnormal in shoulder line angle, blade angle, neck point $\∼$ acromial point $\∼$ scapular point, posterior cervical angle, and upper posterior thoracic angle were increased over age group. The upper body of lateral view was classified into 3 types of posture based on the previous research; straight, erect(leaning back), and stooped(bent forward). The percentiles of subjects who have straight postures were decreased as a function of age, but those of stooped postures were increased. Subjects who have erect postures did not so. The stooped posture group shows the big cervical fossa angle, anterior cervical angle, posterior cervical angle, upper posterior thoracic angle, and the small upper anterior thoracic angle comparing to the straight and erect posture group. These results could be apply for clothing construction reflecting the changes in back, shoulder, neck, and the bilateral asymmetry according to the target age group.
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