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The purpose of this paper is to propose an interactive 2D–3D garment parametric pattern-making and linkage editing scheme that integrates clothing design, simulation and interaction to design 3D garments and 2D patterns. The proposed scheme has the potential to satisfy the individual needs of fashion industry, such as precise fit evaluation of the garment, interactive style editing with ease allowance and constrained contour lines in fashion design.

The authors first construct a parametric pattern-making model for flat pattern design corresponding to the body dimensions. Then, the designing 2D patterns are stitched on a virtual 3D mannequin by performing a virtual try-on. If the customer is unsatisfied after the virtual try-on, the adjustable parameters (appearance parameters and fit parameters) can be adjusted using the 2D–3D linkage editing with hierarchical constrained contour lines, and the fit evaluation tool interactively provides the feedback.

The authors observed that the usability and efficiency of the existing garment pattern-making method simplifies the garment pattern-making process. The authors utilize an interactive garment parametric flat pattern-making model to generate an individualized garment flat pattern that effectively adjust and realize the local editing of the garment pattern-making. The 2D–3D linkage editing is then employed, which alters the size and shape of garment pattern for a precise human model fit of the 3D garment using hierarchical constrained contour lines. Various instances have validated the effectiveness of the proposed scheme, which can increase the reusability of the existing garment styles and improve the efficiency of fashion design.

First, the authors do not consider the garment pattern-making design of sophisticated styles. Second, the authors do not directly consider complex garment shapes such as wrinkles, folds, multi-layer models and fabric physical properties.

The authors propose a pattern adjustment scheme that uses the 3D virtual try-on technology to avoid repetitions of reality-based fit tests and garment sample making in the designing process of clothing products. The proposed scheme provides interactive selections of garment patterns and sizes and renders modification tools for 3D garment designing and 2D garment pattern-making. The authors present the 2D–3D interactive linkage editing scheme for a custom-fit garment pattern based on the hierarchical constraint contour lines. The spatial relationship among the human body, pattern pieces and 3D garment model is adequately expressed, and the final design result of the garment pattern is obtained by constraint solving. Meanwhile, the tightness tension of different parts of the 3D garment is analyzed, and the fit and comfort of the garment are quantitatively evaluated.

To suggest a garment for a wider market, the purpose of this paper is to assess the appearance of garments manufactured by a combination of four methods of flat pattern making and four dress forms from different countries. The paper also compares Japanese and British women’s evaluations of these garments’ appearances.

The authors made 16 garments by combining 4 pattern making methods with measurements from 4 dress forms and evaluated their appearance. The four dress forms were from Japan (Kiiya, called “Kii”), France (Siegel & Stockman, called “St”), the UK (Kennett & Lindsell, called “KL”) and the USA (Wolf Form, called “Wo”), and the four pattern making methods were from Japan (Bunka), Italy (Secoli), France (ESMOD) and the USA (Fashion Institute of Technology, called “FIT”). The authors captured 64 sets of pictures of the 16 garments with the 4 dress forms from the front and the side. The authors then showed images of the four garments made using the same pattern making method with measurements from the four dress forms to subjects for assessment. The subjects – 15 Japanese and 11 British women in their 20s – ranked the pictures in descending order of appearance.

Subjects from both countries rated garments manufactured using the Bunka and Secoli pattern making methods with the Kii and KL dress forms, and those made using ESMOD and FIT with St and Wo as the highest, even though the dress forms used for pattern making and those for wearing were not coincident. On the contrary, many garments made using Bunka and Secoli with St and Wo, and those made using ESMOD and FIT with Kii and KL were rated lowest in terms of appearance, even though the target dress form and wearing dress form were coincident. Therefore, there are appropriate body measurements for each pattern making method that can render the relevant garment more attractive, likely because these measurements are derived from assumed body proportions in the pattern making method of each country.

Although the evaluation of the appearance of garments is an important factor in garment manufacture, scant research has addressed this issue. Moreover, the comparison between Japanese and British women provided here will help manufacturers make garments that are more attractive to people in both countries.

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.

Apparel pattern making creates a set of pattern pieces of fabric which are sewn into the desired garment. The pattern pieces are developed through fashion analysis, pattern design and pattern drafting. Seeks to build an object‐oriented model of the apparel pattern‐making process through these subprocesses. Defines the model in terms of a requirements specification and subsequently uses it in the development of a computerized pattern‐making system. Uses object behaviour analysis, which is derived from object‐oriented technology, as the method for defining the model.

The purpose of the present study was to improve the fit of women’s bifurcated garments by developing an equation that can predict the crotch length accurately by using a few basic body measurements. This equation could provide a simple mass-customization approach to the design of bifurcated garments.

Demographic characteristics and easy-to-record body measurements available in the size USA database were used to predict the crotch length. Different methodologies including best subset regression, lasso regression and principal components regression were experimented with to identify the most important predictor variables and establish a relationship between the significant predictors and crotch length.

The lasso regression model provided the highest accuracy, required only five body dimensions and dealt with multicollinearity. The preliminary pattern preparation and garment fit tests indicated that by utilizing the proposed equation, patterns of customized garments could be successfully altered to match the crotch length of the customer, thereby, improving the precision and efficiency of the pattern making process.

Crotch length is a crucial measurement as it determines bifurcated garment comfort as well as aesthetic fit. The crotch length is usually estimated arbitrarily based on non-scientific methods while drafting patterns, and this increases the likelihood of dissatisfaction with the fit of the lower-body garments. The present study suggested an algorithm that could predict crotch length with 90.53% accuracy using the body dimensions height, hips, waist height, knee height and arm length.

This paper aims to present a flattening method for developing 2D basic patterns from 3D designed garments. The method incorporates the techniques of professional pattern development for the purpose of pattern‐making automation. The aims of the flattening method are to improve the dressing suitability and to produce pleasing figures by reversing design procedures.

A flattening method is presented in this paper for developing 3D undevelopable NURBS surfaces in 2D. The automatic operation embeds the expertise of pattern makers by reducing total area differences between the designed garments in 3D styles and the two‐dimensional patterns. Basic pattern‐making invokes the boundary constraints which apply mesh alignments techniques.

The global area difference between the original 3D designs and the 2D‐developed pattern is controlled within 5 percent in order to reach the final outcomes of basic patterns, whose shapes are similar to the drawing patterns currently utilized in the industry.

This study currently handles simple designs, such as basal designs, and can only flatten garments in symmetric styles. The direct flattening method is developed by this study. In addition, this study is supplemented by expert‐based knowledge, and it establishes basic boundary conditions for various garment patterns to increase the feasibility of flattening automation.

This study introduces the fundamental theories and methodologies used in the automatic making of basic patterns from 3D garment designs. It proposes a flattening method with pattern expertise embedded by real‐time approximations of the global area of the 3D undevelopable designs to the 2D patterns.

The purpose of this paper is to build a mathematical model of men’s wear prototype, so that the computer can draw men’s wear prototype automatically.

First, the bust line, front and back center line, waist line, side seam, front chest width and back width line in the coordinate system are expressed by equations. Then, a parabola is used to establish a neckline curve, a linear equation is used to establish a shoulder oblique line, and a double ellipse is superposed to construct the armhole arc. Finally, all the garment prototype curves are built mathematical models.

The result shows that every curve of garment prototype can be expressed approximately by mathematical model.

This research lays the foundation for the automation and intelligence of garment pattern-making.

The main purpose is to construct the mapping relationship between garment flat and pattern. Particle swarm optimization–least-squares support vector machine (PSO-LSSVM), the data-driven model, is proposed for predicting the pattern design dimensions based on small sample sizes by digitizing the experience of the patternmakers.

For this purpose, the sleeve components were automatically localized and segmented from the garment flat by the Mask R-CNN. The sleeve flat measurements were extracted by the Douglas–Peucker algorithm. Then, the PSO algorithm was used to optimize the LSSVM parameters. PSO-LSSVM was trained by utilizing the experience of patternmakers.

The experimental results demonstrated that the PSO-LSSVM model can effectively improve the generation ability and prediction accuracy in pattern design dimensions, even with small sample sizes. The mean square error could reach 1.057 ± 0.06. The fluctuation range of absolute error was smaller than the others such as pure LSSVM, backpropagation and radial basis function prediction models.

By constructing the mapping relationship between sleeve flat and pattern, the problems of the garment flat objective recognition and pattern design dimensions accurate prediction were solved. Meanwhile, the proposed method overcomes the problem that the parameters are determined by PSO rather than empirically. This framework could be extended to other garment components.

Identifies a set of manufacturing data interfaces that could be standardized for the effective computer integration of the information required to operate an apparel manufacturing enterprise. The interfaces are called Application Protocols. Describes a method using pieces of information, referred to as Units of Functionality, as building blocks for designing Application Protocols.

The purpose of this study is to explore fit problems, satisfaction and preferences of Ethiopian male consumers of ready-made garments (shirt, polo shirt, sweater and khaki and jeans trousers) and highlight the need for a domestic standard garment size chart.

Using a structured questionnaire, 405 usable responses were collected from consumers in four cities (Bahir Dar, Kombolcha, Dessie and Addis Ababa) based on convenience sampling. Moreover, the pattern-making methods of 12 domestic garment manufacturing companies were investigated. One-way analysis of variance and multivariate analysis of variance were used to examine differences in fit satisfaction with age, body size and shape. Multiple regression was used to test hypotheses.

The participants were mostly neither satisfied nor dissatisfied with the fit of the garments irrespective of their age, body size and shape. While age was found to be insignificant, apparel sizes worn and body shape were found to be significant predictors of fit type in most garments. It was also found that most of the domestic garment manufacturing companies use the knock-off method for pattern making, which results in a bad fit as the basic garment for the knock-off is constructed based on other countries’ standards.

This study investigates the fit problems and preferences of ready-made garments in the context of consumers in a developing country. Moreover, it has a contribution in considering men’s body shape in the analysis of fit preferences. The results have implications for developing domestic standard garment size charts to improve fit satisfaction.