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The seams of slim fit outdoor pants can be uncomfortable or even restrict body movement. To reduce discomfort, the authors need to determine optimal cutting lines in various designs that do not interfere with body movement. The purpose of this paper is to apply skin deformation mapping during movement to the ergonomic design of outdoor pants, focusing in particular on the 2D pattern generation of the crotch area in a 3D shape during movement.

A 3D shape and skin length deformation of the lower body were observed, including the crotch area, which is difficult to examine on the human body. To design ergonomic and streamlined outdoor pants, the authors selected seam lines where the changes in skin deformation are at their minimum based on the skin deformation mapping. In addition, the inseam along the medial thigh close to the crotch was removed to adjust the skin length of these areas, thereby increasing the extensible area of fabric necessary to adjust to a skin deformation. After selecting the seam lines, each of the 3D pattern blocks was generated by means of a 2D flattening method. In addition, the stress distribution of overlapped replica blocks along the crotch line during the 2D flattening process is a main independent factor to avoid deteriorating lower body movement as well as a good appearance.

Based on the results of skin deformation mapping of a human subject, this study suggested that it is best that the design line crosses where there is no skin deformation possible. And the pants were developed without the inner seam line at the upper medial thigh because of skin deformation of a large range of ±6 percent in the upper medial thigh during a 90° knee flexion or in the squatting down position. In a wear test, the developed 3D pattern without an inseam was rated higher than that with an inseam. This verified that removing the inseam, to prevent skin deformation of the medial upper thigh during knee flexion and squatting, is a logical decision. Regarding the correction of the overlapping area during arrangement of the replica, the appearance of the front of the pants was improved when 80 percent of the overlapping area was distributed near the point of the error source, which is the front of the male’s crotch line.

In this study, the crotch area, which has been difficult to observe in previous studies, were observed thoroughly and it was found that the length of the crotch curve did not increase during movement. In addition, skin deformation was mapped during a 90° knee flexion or in the squatting down position. It is expected that the overall process of developing 3D streamlined outdoor pants from 3D skin deformation mapping can be expanded to the development of patterns for other customized functional pants.

The purpose of this paper is to analyze the fit and thermal and moisture comfort factors to provide some reference value for the functional design of underwear.

The body size data of 100 male youths are measured to analyze the body shape of the lower body. Based on the complete body size, the authors selected the matching underwear, and obtained the relevant data for the mathematical model of thermal and moisture using Grey correlation analysis method.

In allusion to the defect of fit comfort and thermal-moisture comfort of the crotch, this paper presented a mathematical model, and experimental results showed that breathable fabric and breathable volume are the key factors.

It was clarified that which is the key to the thermal and moisture comfort. At the same time, male lower body characteristics index is clear.

The purpose of this paper is to focus on solving a fit problem associated with female pants by taking into account the body shape of crotch curves. The patterns of customized pants could be altered with the distance ease (DE) distribution along the crotch curve.

Four pairs of pants with different crotch ease allowances were designed based on a standard mannequin, and used to study how the DE was distributed along the crotch curve at a given ease allowance. The unclothed mannequin and the four pants, which were dressed, respectively, on the mannequin, were scanned consecutively by a body imaging system. The crotch curve of the unclothed mannequin was superimposed on that of each clothed mannequin to exhibit the differences in radial distance so that the DE distribution could be measured.

Through the regression analysis, the prediction models were established to express the relationships between the DE and the ease allowance. These models could be used to estimate the DEs along a crotch curve to reflect its asymmetrical shape when a total allowance was selected. The crotch curves on the pant patterns could be then modified by adding the predicted DEs to the scanned crotch curve.

This study demonstrated a new pattern alteration approach to achieve a better fit for customized female pants based on the 3D scanning data. This approach can be extended to pattern alterations for men’s pants and other shape-critical products.

The purpose of this paper is to develop an automated custom-pattern-making system using the width-height independent grading method for semi-customized clothing.

The system reads basic patterns and graded large patterns and calculates the grading ratio of independent horizontal and vertical values on all points in a pattern. The custom pattern is automatically generated by calculating the horizontal and vertical grading amount according to individual body measurements. The system does not follow any complicated alteration rules.

The width-height independent grading method can provide custom-pattern fitted primary body circumference and length and helps to quickly produce semi-customized clothing.

There are few studies on automated custom-pattern-making systems without an alteration rule. This study developed an automatic custom-pattern-making system using the width-height independent grading method.

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.

This study investigated fashion involvement, pre‐purchase clothing satisfaction and clothing needs of petite and tall‐sized consumers. The differences between petite and tall‐sized consumers were compared, and the relationship among the three variables was examined. Petite and tall‐sized women's shopping characteristics were identified. The data were obtained through mail survey method. The final sample consisted of 177 petite and 144 tall women. Data were statistically analysed to fulfil the purpose of the study. Descriptive statistics, such as frequency, mean and standard deviation, were utilised to define the characteristics of the sample. Analysis of variance was tested to compare beliefs about clothing attributes. T‐test and analysis of covariance were utilised to determine if there is any difference between petite and tall women in terms of fashion involvement, pre‐purchase clothing satisfaction and clothing needs. Pearson Product Moment Correlation and Pearson Partial Correlation Coefficient were utilised to test the hypotheses. The results indicated significant but relatively low relationships among fashion involvement, pre‐purchase clothing satisfaction and clothing needs. Fashion involvement and clothing needs were positively correlated, while pre‐purchase clothing satisfaction and clothing needs were negatively correlated for both petite and tall‐sized women.

The purpose of this paper is to improve the prediction accuracy of the body shape prediction model and provide some reference value for the design of underwear.

The body size data of 250 male youths is measured to analyze the body shape of the lower body. And there is a total of 56 measurement items, which are clustered by GA-BP-K-means, K-means, optimal segmentation method for ordered samples, wavelet coefficient analysis, regression analysis and Naive Bayes Algorithm. Finally, a test male sample of an unknown body shape was clustered to verify the superiority of the GA-BP-K-means.

This paper presented the key factors for body shape clustering, and experimental results have shown that the GA-BP neural network model is higher in speed and precision than other algorithm prediction models.

It was clarified which is the key to body shape clustering. At the same time, the GA-BP-K-means algorithm can promote the popularization and application of the prediction model in body shape clustering.

Most apparel sizing systems are based on one or two body dimensions and rely on assumptions about proportional body relationships to project other dimensions necessary to design the garment pattern. Garments from these systems will not fit a population with large variations in body proportions. Using nonlinear optimization methods and anthropometric data of US Army women three multidimensional sizing systems were derived that are designed to provide improved fit for women from the USA, a population with much variation. These systems range from an optimized linear system with a regular grade to an unconstrained optimized system with a grade break at each size. The optimized sizing systems compare favorably with D5585‐94 in their ability to accommodate variation in the population based on a mathematical test of the aggregate loss of each system. Issues related to pattern grading, size selection, and calculation of stock keeping units are discussed.

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.

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.