Bingfei Gu, Wenping Lin, Junqiang Su and Bugao Xu
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Bingfei Gu, Junqiang Su, Guolian Liu and Bugao Xu
The goal of this study was to realize pattern alterations for women’s suits by using the spatial distribution of distance ease in the body-garment interface.
Abstract
Purpose
The goal of this study was to realize pattern alterations for women’s suits by using the spatial distribution of distance ease in the body-garment interface.
Design/methodology/approach
An unclothed mannequin and the mannequin clothed with seven suits having different ease allowances were scanned by a 3D body scanner respectively. The image of the unclothed mannequin was then superimposed on that of each clothed mannequin (suit) to exhibit the differences in ease distribution among these suits. The distance eases at ten selected body landmarks were determined by measuring the gaps between the body and suit surfaces.
Findings
The mathematical models of ease distributions were built through the regression analysis to predict the distance ease with a given ease allowance. After the verification with the actual measurements, these ease distribution models could provide localized distance eases for alternating pattern pieces to ensure a specified ease allowance.
Originality/value
In order to realize the automatic generation of garment patterns, the ease distribution between a human body and a garment is crucial because ease is one of the determinants for garment fit. This study demonstrated a new approach of automatic pattern alteration based on 3D scanned data to accelerate the pattern making process for women’s suits with customized ease allowance.
Xinrong Hu and Bugao Xu
The purpose of this paper is to develop a fast parameterized modeling approach to generate individualized dress forms for realistic human bodies.
Abstract
Purpose
The purpose of this paper is to develop a fast parameterized modeling approach to generate individualized dress forms for realistic human bodies.
Design/methodology/approach
An individualized dress form is created by deriving a new set of fitting functions from a number of key existing dressing parameters and pre‐defined templates. The fitting functions only contain simple shapes of circular and/or elliptical arcs, which can be modified computationally based on a few personal dressing data.
Findings
This paper reaffirms that individual body shape can be adequately described by a number of critical cross‐section silhouettes, and a personalized dress form can be constructed based on key dressing parameters and templates.
Originality/value
The fitting functions and relevant dressing data for specific cross‐sectional silhouettes are determined, permitting a user to create personalized dress forms only by inputting a simple set of dressing parameters.
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Junqiang Su, Bingfei Gu, Guolian Liu and Bugao Xu
– 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.
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Social implications
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.
Originality/value
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.
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Yueqi Zhong and Bugao Xu
This paper presents methods and algorithms to automatically segment and measure the human body.
Abstract
Purpose
This paper presents methods and algorithms to automatically segment and measure the human body.
Design/methodology/approach
In the segmentation procedure, two different methods are designed to find the crotch point for the situation of non‐contacted thigh and contacted thigh, respectively. Three different methods: minimum distance algorithm, minimum inclination angle algorithm, and directional neighbor identification algorithm are introduced to search the branching points or triangle. In the body measurement procedure, a pre‐sorted circling method is designed for circumference measurement, and the basic principle of landmark acquisition has been discussed. These techniques are validated via testing over different type of scanned model.
Findings
The results of automatic segmentation and body measurement have verified that our methods are efficient and versatile in processing different type of scanned body.
Research limitations/implications
The accurate and automatic locating of wrist, ankle and knees contour can be more difficult than it appears to be.
Practical implications
The main usage of scanned body in our research is for 3D garment try‐on.
Originality/value
This paper introduces the methods for crotch identification, and the methods including minimum distance algorithm, minimum inclination angle algorithm, and directional neighbor identification algorithm for human body segmentation. It also explains the fundamental measuring techniques, and outlines the results of using these techniques in segmentation and measurement.
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Junqiang Su, Guolian Liu and Bugao Xu
– The purpose of this paper is to concentrate on the development of individualized prototype of apparel patterns for young females from 3D body scanning data.
Abstract
Purpose
The purpose of this paper is to concentrate on the development of individualized prototype of apparel patterns for young females from 3D body scanning data.
Design/methodology/approach
The authors presented a new pattern-making approach that is composed of three major steps: to establish the relationships between body features and corresponding elements in a prototype (e.g. curve or a point); to classify the relationship into grades that provide alternatives to fit a variety of bodies; and to assemble each individual element into a personalized prototype.
Findings
The experiment demonstrated that this method could be used for customized prototype development from 3D body scanning in a relatively easy way.
Research limitations/implications
Currently, the subjects of this study included only Chinese young females, and the regression models were just suitable for the similar body types though, the research method could be extended to other somatotypes and age groups.
Social implications
This approach can be used in the field of made-to-measure, mass customization, and the quick response for apparel pattern making. The technology in this paper facilitates to generate an individualized pattern prototype from 3D body scanning data.
Originality/value
Originated from the relationship between the features of a human body and the elements of a pattern prototype, the authors presented a new approach to develop an individualized pattern prototype by classifying the features into grades.
Details
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The intelligent identification of stains can quickly and accurately identify stains. At present, stains are identified subjectively by appearance, color, taste, feel, location…
Abstract
Purpose
The intelligent identification of stains can quickly and accurately identify stains. At present, stains are identified subjectively by appearance, color, taste, feel, location, etc. Color is an important factor in identifying stains. K/S value is used to analyze the color of textile fabric, and it has additivity. The purpose of the study is to explore its application in stain recognition is of great significance to intelligent washing.
Design/methodology/approach
A certain method used to stain the textile, then the K/S value of the textile before and after the stain was analyzed and tested by the color difference instrument. The K/S curve of the stain was calculated by the addition of K/S, and then the stain was identified and distinguished.
Findings
The K/S value of the textile stained with stains could be deducted by the K/S value of the color difference meter. After deducting the base cloth, the K/S curve of the same stain is basically the same. Then the stain can be identified and analyzed.
Research limitations/implications
The K/S value can be used for stain analysis, but it needs to be analyzed and tested in the laboratory.
Practical implications
This study provides a simple method for stains identification.
Originality/value
In addition to common methods of stain identification, such as appearance, color, feel, smell, location, stain removal materials, breaking the substrate, IR, etc., K/S value can be used for stain analysis. Identifying stains and washing them in a targeted way to achieve a better washing effect could provide certain technical support for the development of smart washing and smart home appliances.