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This paper presents a method to fabricate a fitting-mannequin using 3D-scanning, modeling and printing technologies.

Scan data were obtained from 12 subjects with body size in the average range, selected from 208 women aged 20–29. The 3D-scan data were modified by selecting cross-sections from the cloud data, symmetrizing body shapes and obtaining mean points of body shapes. Fifteen spline curves, generated by connecting the mean points on the X–Y plane, were used as sketches and loft features to create the 3D mannequin models. A lower-body fitting mannequin was printed with polylactic acid plastic using a fused deposition-modeling 3D printer.

The cross-section circumference discrepancies among the 3D-printed mannequins in each step were within 1%, demonstrating the applicability and reliability of the 3D technologies proposed for mass customization.

The proposed methodology demonstrates the value of using 3D-scanning data to manufacture fitting-mannequins via mass customization. The study demonstrates the possibility and practicality of using 3D techniques to produce commercially viable fitting mannequins for the fashion industry.

The purpose of this paper is to focus on the determination of distance ease of pants from the 3D scanning data of a clothed and unclothed body.

A human model whose body size conformed to the Chinese dummy standard and four pairs of suit pants were chosen for the study. The scanned surfaces of both the body and the pant were superimposed based on the preset markers. The circumferences at four important positions – abdomen, hip, thigh and knee – were selected for pant ease determination. At one position (e.g. hip), the two cross-sections were divided into several characteristic sections and the distance ease, i.e. the space between the cross-sections at each section was measured. The regression equations between the distance ease and ease allowance were then derived so that the distance ease can be estimated.

The relationship was found between the distance ease and the ease allowance. Meanwhile, a mathematic model was established to convert the distance ease into the increments of a pant pattern, which helps to develop an individual pant pattern automatically.

The paper provided the concept and the method to customize a pant by using the 3D scanning data of body. It created a link between the 3D distance ease and the 2D ease allowance, and the model to calculate the distance ease increments which warrant proper ease distributions. The method helps to develop an individualized garment pattern automatically from a basic and tight pant pattern.

Understanding the relationship between the distance ease and the ease allowance and increments of pattern could help develop an individual apparel pattern from 3D measurements. This paper showed a way to solve the problem of distribution of the apparel ease in a virtual environment and convert body measurements from a 3D scanner into personalized apparel patterns.

This paper aims to describe the development of a method of constructing three‐dimensional (3D) human body shapes that include a degree of ease for purpose of computerized pattern making.

The body shape could be made with ease allowance to an individual's unique body shape using sweep method and a convex method. And then generates tight skirt patterns for the reconstructed virtual body shape using a computerized pattern making system.

This paper obtains individual patterns using individually reconstructed 3D body shapes by computerized pattern development. In these patterns, complex curved lines such as waist lines and dart lines are created automatically using the developed method. The method is successfully used to make variations of a tight skirt to fit different size women. The author also used the method to make other skirts of various designs.

The method described in this paper is useful for making patterns and then garments, without the need for the garments to be later adjusted for the subject.

We aimed to establish criteria for determining the deformed lateral torso type to identify individuals requiring measurement methods different from standard methods before extracting dimensions from three-dimensional (3D) scan data.

We collected the 3D body scan data of 119 women aged 70–85 years collected in the 6th Size Korea. Three axes were defined to determine the deformation of the lateral shape, and the angle of each reference axis was used for the analysis. Additionally, to classify the lateral torso shape, 14 experts made visual judgments on the side-view images of the participants.

To identify the axis that best represented the lateral torso shape, we used each angle value of the three reference axes as an independent variable and the expert’s visual classification as a dependent variable. Each discriminant function was obtained and accuracy calculated. The whole torso axis exhibited the highest accuracy. Next, an assessment scale was developed to determine the shape of the lateral torso using the angular value of the whole torso axis.

The scale developed in this study has the potential to reduce measurement errors arising from elderly deformed torso shapes, thereby enhancing data reliability.

This research aims to collect human body variables via 2D images captured by digital cameras. Based on those human variables, the forecast and recommendation of the Digital Camouflage Uniforms (DCU) for Taiwan's military personnel are made.

A total of 375 subjects are recruited (male: 253; female: 122). In this study, OpenPose converts the photographed 2D images into four body variables, which are compared with those of a tape measure and 3D scanning simultaneously. Then, the recommendation model of the DCU is built by the decision tree. Meanwhile, the Euclidean distance of each size of the DCU in the manufacturing specification is calculated as the best three recommendations.

The recommended size established by the decision tree is only 0.62 and 0.63. However, for the recommendation result of the best three options, the DCU Fitting Score can be as high as 0.8 or more. The results of OpenPose and 3D scanning have the highest correlation coefficient even though the method of measuring body size is different. This result confirms that OpenPose has significant measurement validity. That is, inexpensive equipment can be used to obtain reasonable results.

In general, the method proposed in this study is suitable for applications in e-commerce and the apparel industry in a long-distance, non-contact and non-pre-labeled manner when the world is facing Covid-19. In particular, it can reduce the measurement troubles of ordinary users when purchasing clothing online.

In order to present a significant usage of the computer-aided design (CAD)/computer-aided manufacturing (CAM) systems in the apparel and textile industry, the current literature has been observed. Although the CAD/CAM systems have also been increasingly applied to all fields apparel and textile manufacturing for the last few decades, improving the precision, productivity and the organization of the information flow, they have not been fully utilized in these industrial fields. The paper aims to discuss these issues.

The paper is structured in three main sections showing the vast applicability of the CAD/CAM systems, the benefits provided by them and the future trend in their development.

Although the initial development of the CAD/CAM systems strived to completely eliminate manual and time-consuming operations, they have not been accepted in practice due to their inflexibility at making changes and the time needed for regenerating a complex parametric model. The textile and apparel industries show slow progress in acquiring the CAD/CAM systems.

This CAD/CAM technology enabled the customization in the design process according to individual needs and directed the textile and the apparel industry to moving into new directions such as the mass customization to personalization. The paper makes clear that although this technological concept is rather old, the use of the CAD/CAM systems will inevitably broaden in terms of applicability to new production stages.

The purpose of this paper is to develop a “good fit” for garments for customer satisfaction, comfort, and functionality as well as a manufacturer's success and reputation.

This paper reviews and evaluates garments on a live fit model and makes recommendations for the acceptance or modification of the garment for production. As more manufacturing, product development, and designing responsibilities continue to take place globally, alternatives to the traditional fit analysis are under consideration.

Fit analysis using live and three‐dimensional scan models as an alternative to the traditional fit analysis are under consideration.

This paper evaluates garments on a live fit model and makes recommendations for the acceptance or modification of the garment for production.

New techniques are required to link 3D whole body scans to manufacturing techniques to allow for the mass‐customization of clothes. This study aims to compare two methods of producing skirts based on 3D whole body scans.

Three females participated in the study. They were scanned with an accurate 3D whole body scanner. A set of relevant 1D measures was automatically derived from the 3D scan. The measures were incorporated in a skirt pattern and the skirt was made from jeans material. The second method was based on triangulation of the scanned waist‐to‐hip part. The points in the 3D scan were first converted to triangles and these triangles were thereafter merged with neighboring triangles of similar orientation until about 40 triangles remained. These triangles were sewn together to form a “patchwork”‐skirt. All females performed fit tests afterwards.

The fit of the 3D‐generated patchwork skirt was much better than the fit of the skirt generated by the 1D scan‐derived measures. In the latter case, two of the three skirts were too wide because the scan‐derived hip circumference exceeded the manually derived values. For the 3D generated skirt, it was necessary to enlarge the triangles with a factor of 1.025 to achieve optimal fit.

As far as is known, this is the first study that reports a direct conversion of a 3D scan to clothing without interference of clothing patterns. The study shows that it is possible to generate a fitting patchwork skirt based on 3D scans; the intermediate step of using 1D measures derived from 3D scans is shown to be error‐prone.

Currently, a common method of reconstructing mannequin is based on the body measurements or body features, which only preserve the body size lacking of the accurate body geometric shape information. However, the same human body measurement does not equal to the same body shape. This may result in an unfit garment for the target human body. The purpose of this paper is to propose a novel scanning-based pipeline to reconstruct the personalized mannequin, which preserves both body size and body shape information.

The authors first capture the body of a subject via 3D scanning, and a statistical body model is fit to the scanned data. This results in a skinned articulated model of the subject. The scanned body is then adjusted to be pose-symmetric via linear blending skinning. The mannequin part is then extracted. Finally, a slice-based method is proposed to generate a shape-symmetric 3D mannequin.

A personalized 3D mannequin can be reconstructed from the scanned body. Compared to conventional methods, the method can preserve both the size and shape of the original scanned body. The reconstructed mannequin can be imported directly into the apparel CAD software. The proposed method provides a step for digitizing the apparel manufacturing.

Compared to the conventional methods, the main advantage of the authors’ system is that the authors can preserve both size and geometry of the original scanned body. The main contributions of this paper are as follows: decompose the process of the mannequin reconstruction into pose symmetry and shape symmetry; propose a novel scanning-based pipeline to reconstruct a 3D personalized mannequin; and present a slice-based method for the symmetrization of the 3D mesh.

The purpose of this paper is to present results of shape analysis of female torso shape using the discrete cosine transform (DCT) from a three-dimensional (3D) whole body scan database.

Torso shape is a central part of body shape and difficult to describe by linear measurements. In order to analyze body shape variation within a population the authors employed a DCT-based shape description method to compresses a dense 3D body scan surface into a small vector that preserves shape and removes size. The DCT-based shape descriptors of torso surfaces are further fed to principal component analysis (PCA) that decompose shape variation into constituent shape components. A visualization program was developed to observe principal components of torso shape and interpret their meanings.

Extreme shapes of the first ten principal components summarize major shape variations and identify shapes that are difficult to capture with traditional anthropometric measurements. PCA results also help to find and retrieve similar shapes from a population-level database.

Using the DCT for PCA of torso shape is a unique and original approach. It provides a basis for the description and classification of torso shape in 3D and the results from the shape analysis are potentially useful for designers of clothing and personal protective equipment.