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With the use of 3D body scanners, body measurement techniques can be non‐contact, instant, and accurate. However, how each scanner establishes landmarks and takes the measurements should be established so that standardization of the data capture can be realized. The purpose of this study was to compare body‐scanning measurement extraction methods and terminology with traditional anthropometric methods. A total of 21 measurements were chosen as being critical to the design of well‐fitting garments. Current body scanners were analyzed for availability of information, willingness of company cooperation, and relevance to applications in the apparel industry. On each of the 21 measurements, standard measurement procedure was identified for three different scanners: [TC]², Cyberware, and SYMCAD. Of the 21 measures in the study, [TC]² was the scanner that had the most measures identified for the study and also had the capability of producing many more with specific application for apparel.

The purpose of this paper is to develop an automated human body measurement extraction system using simple inexpensive equipment with minimum requirement of human assistance. This research further leads to the comparison of extracted measurements to established methods to analyze the error. The extracted measurements can be used to assist the production of custom-fit apparel. This is an effort to reduce the cost of expensive 3-D body scanners and to make the system available to the user at home.

A single camera body measurement system is proposed, implemented, and pilot tested. This system involves a personal computer and a webcam operating within a space of controlled lighting. The system will take two images of the user, extract body silhouettes, and perform measurement extraction. The camera is automatically calibrated using the software each time of scanning considering the scanning space. The user will select a front view and a side view among the images captured, and specify the height. In this pilot study, 31 subjects were recruited and the accuracy of 8 human body measurements were compared with the manual measurements and measurements extracted from a commercial 3-D body scanner.

The system achieved reasonable measurement performance within 10 percent accuracy for seven out of the eight measurements, while four out of eight parameters obtained a performance similar to the commercial scanner. It is proved that human body measurement extraction can be done using inexpensive equipment to obtain reasonable results.

This study is aimed at developing a proof-of-concept for inexpensive body scanning system, with an effort to benchmark measurement accuracy, available to an average user providing the ability to acquire self-body measurements to be used to purchase custom-fit apparel. This system can potentially boost the customization of apparel and revolutionize online shopping of custom-fit apparel.

This study establishes the principles and process steps of a new basic trousers pattern using measurements obtained according to the rules of the anthropometric measurement system. The newly developed pattern-making system in this study will be called the “Anthropometric Measurements Based Pattern Making System” (AnMePa). It is aimed at producing trousers that are more fitting to the body, thanks to this pattern-making system.

In this research, four pattern-making systems used in many parts of the world were compared with the “Anthropometric Measurements Based Pattern Making System” (AnMePa) with regard to the overall appearance and body fit of trousers prepared according to these systems. 10 virtual mannequins (VM) with different adult female body measurements were created, and trousers patterns were prepared for these mannequins. The trousers’ patterns were made and dressed on the mannequins in a 3D virtual dressing system. The body fit of the virtual garments was evaluated by five experts. The scores given by the experts were evaluated using the fuzzy logic method.

According to the results, it is seen that the new basic trousers pattern developed by utilizing the anthropometric measurement system, AnMePa, provides the best body fit among the basic trousers patterns created according to the other examined pattern-making systems. The combination of 3D virtual dressing and fuzzy logic in the evaluation of garment body fit is considered an innovative method for the future of fashion design and production.

In the developed AnMePa, unlike the existing pattern-making systems, values that can be associated with the body measurements of individuals in a way that could be suitable for each community were used instead of constant values in the pattern-making process. Furthermore, the integration of 3D virtual fitting and fuzzy logic in assessing garment fit is considered a pioneering approach with significant implications for the future landscape of fashion design and production.

Two-dimensional (2D) measurement technology has become more popular than before, thanks to the widespread availability of smartphones and smart devices. However, most existing 2D body measurement systems have background constraints and may raise privacy concerns. The purpose of this research was to test the idea of designing a 2D measurement system that works with a color-coded measurement garment for background removal and privacy protection. Clothing consumers can use the proposed system for daily apparel shopping purposes.

A 2D body measurement system was designed and tested. The system adopted a close-fitted color-coded measurement garment and used neural network models to detect the color-code in the garment area and remove backgrounds. In total, 78 participants were recruited, and the collected data were split into training and testing sets. The training dataset was used to train the neural network and statistical prediction models for the 2D system. The testing dataset was used to compare the performance of the 2D system with a commercial three-dimensional (3D) body scanner.

The results showed that the color-coded measurement garment worked well with the neural network models to process the images for measurement extraction. The 2D measurement system worked better at close-fitted areas than loose-fitted areas.

This research combined a color-coded measurement garment with neural network models to solve the privacy and background challenges of the 2D body measurement system. Other researchers have never studied this approach.

To obtain sizing systems a specialist knowledge is required to analyse statistically body measurements from surveys. Control measurements, size ranges, body proportions and size intervals have to be calculated. A survey of 100 young women was undertaken in 1993/93 at Manchester Metropolitan University and 10 body measurements were taken. This is used to illustrate the statistical analysis of body measurements, the formulation of sizing systems and body measurement tables. A review of previous surveys and their methods of analysis was undertaken. The main control measurements of height, bust, waist and hips denoting the size of the wearer were obtained by correlation. Size ranges and intervals were obtained by normalising the data and comparing the sizes young women bought and previous size charts. Sizing systems for five sizes 8 to 16 were suggested for three heights, short, medium and tall and bust fittings medium, small and very small. This retained the same proportion for the five sizes within each of the nine systems. A further system of changing proportion in girth measurements was developed from the survey of young women based on percentiles and bust fittings. The neck girth which did not correlate strongly with any measurement was analysed separately. Two examples of body measurement tables covering 30 measurements were formulated to illustrate the procedure. Analysing body measurements statistically is problematic especially in small surveys. It is hoped the suggested guidelines will clarify this area. The coding of sizes is still not uniform. A comparison was made with previous tables. It was concluded that the body proportion had changed and the young women were taller and broader in the waist and hips. Part 3 of this study will cover comparing the problems of taking accurate body measurements with different equipment, formulating size charts for different garments and fabrics and relating these to different systems of pattern construction, and finally, testing prototype garments for size and fit.

This research aimed to develop an automatic 3D body measurement line generation method that reduces errors induced by diverse body shapes and incomplete scan areas.

Three-dimensional body scan data from the 5th Size Korea database were used. Measurement extraction methods were developed for each measurement; chest girth, underbust girth, armscye girth and neck base girth.

The research showed that the method adopted in this study enhanced the accuracy of the scan measurements for various body shapes and incomplete scan data. The authors verified the accuracy of the developed methods for various body shapes by comparing the scan measurement against manual measurement.

The automatic 3D body measurement line generation algorithms developed for various human body shapes will improve the reliability and accuracy of 3D body scan measurement program. Also. it will be of practical use in human-size-related production processes.

The purpose of this paper is to validate the accuracy of point cloud data generated from a 3D body scanner.

A female dress form was scanned with an X‐ray computed tomography (CT) system and a 3D body scanning system. The point cloud data from four axial slices of the body scan (BS) data were compared with the corresponding axial slices from the CT data. Length and cross‐sectional area measurements of each slice were computed for each scanning technique.

The point cloud data from the body scanner were accurate to at least 2.0 percent when compared with the CT data. In many cases, the length and area measurements from the two types of scans varied by less than 1.0 percent.

Only two length measurements and a cross‐sectional area measurement were compared for each axial slice, resulting in a good first attempt of validation of the BS data. Additional methods of comparison should be employed for complete validation of the data. The dress form was scanned only once with each scanning device, so little can be said about the repeatability of the results.

Accuracy of the point cloud data from the 3D body scanner indicates that the main issues for the use of body scanners as anthropometric measurement tools are those of standardization, feature locations, and positioning of the subject.

Comparisons of point cloud data from a 3D body scanner with CT data had not previously been performed, and these results indicate that the point cloud data are accurate to at least 2.0 percent.

A survey of 100 young women's body measurements was undertaken during 1992/93. The findings are the basis of Part 3, which aims to explain how size charts are developed for garments; to evaluate the measuring equipment used and to compare the size chart body measurements with those proportionally derived by traditional formulae. A size chart is the artificial dividing of a range of measurements which are concise and consistent. There are different types of size charts. Some are of body measurement for specific proportion and shape. Others are for garments including ease allowances which vary according to the garment style and type of fabric. Size charts can be developed in three stages commencing with the raw survey data, which is then rounded to the nearest 1.0 cm or 0.5 cm and finally ease allowance is added for the finished garment. During the survey some measurements were repeated using different measuring equipment so that a comparison could be made to select the most suitable for pattern construction. The use of the anthropometer is limited as it can only take linear measurements. However, it is helpful when analysing body proportion, whereas the tape measures attached to the harness and a metal tape measure can record the contour surface of the body, which is more appropriate for clothing. The adjustable square and angle were a little difficult to position correctly but were useful to check the formulae used for pattern construction. A comparison is made between the survey body measurements and traditional formula to derive body measurements which are difficult to take. The dividing of the height by eight heads is useful for length proportions. The derived neck shape and survey measurements were comparable. Head measurements suitable for hoods were similar for all bust and neck sizes. Only the height showed any progression in size. This concludes the three articles which explain the taking of body measurements, methods of analysing the data and applying it to clothing pattern construction. It is hoped that this will aid those in industry and education who wish to undertake research and to develop new technology.

The purpose of this paper is to analyze petite women’s body size and figure and investigate whether current petite sizing charts accurately reflect actual petit size women’s bodies. This study also categorizes petite women’s body shapes and suggests primary body measurements as a base size for each shape. The ultimate goal is to suggest fundamental body measurements for apparel companies to modify and improve their sizing.

This study used data from SizeUSA data to compare body measurements of 18-35-year-old petite women to regular women. The authors compared the results to measurement differences between petite and regular sizing charts of 14 apparel companies. Then, using the principal component analysis and cluster analysis, the authors classified petite women’s body shapes. Body measurements for each body type are contrasted with the current petite sizing charts, and then, the authors present differences as suggestions for modification and improvement of petite sizing.

Industry sizing system do not generally represent average petite size women preciously except for stature. Within the petite women, four body types were identified (top petite: 30.0 percent, bottom petite: 30.8 percent, regular petite: 23.6 percent, and plus size: 15.4 percent). Of the four groups, the ASTM D7878 generally represented the “top petite” sizing.

It is the first to analyze the industry petite sizing system utilizing population data and focus petite sizing for women aged 18-35. The authors believe this study could draw attention of the apparel industry, providing companies with ideas of how to improve their petite sizing for young women.

A two-dimensional (2D) body measurement system was implemented to study the application of sportswear design in measurement garment development. A total of 50 participants were recruited. The basic demographic information and sportswear preference data were collected through a survey to understand consumer preferences and acceptance of the new designs. The body measurements were collected through both the selected 2D measurement system and a commercial three-dimensional scanning booth to evaluate measurement accuracy.

Finding the right size has been a long-existing problem for clothing consumers. Size problem is the most common reason for e-commerce returns and adds a high cost for retailers. One possible solution is to offer consumers an easy-to-use method that extracts accurate body measurements to be used for clothing size selection. The purpose of this research is to apply sportswear design elements on measurement garments to see if consumers’ interest in using the 2D measurement system can be increased without influencing the measurement accuracy.

The results showed that the added design features increased consumers’ interest in using 2D body measuring technology without significantly influencing measurement accuracy.

This research applied sportswear elements to convert a 2D measurement bodysuit to a fashionable clothing product. The solution resolved users’ privacy concerns and increased their acceptance and use of the technology. Other studies have not focused on using aesthetic features to improve the 2D measurement technology.