Search results

Body type classification has a great influence on plate making and garment sizing system, and the accuracy of body type classification method will greatly affect the fit of garment production. The purpose of this paper is to use the decision tree algorithm to study body classification rules, develop a decision tree body recognition model and judge the body shape of middle-aged women in Xinjiang.

First, perform dimensionless processing on the collected data of 256 middle-aged women in Xinjiang, and the dimensionless data were used for K-means body clustering; Then, quantitatively analyze the effectiveness of different classification clusters based on the silhouette coefficients. Second, the decision tree algorithm is used to divide the classified sample data into a training set and a test set at a ratio of 70/30, and select the best node and the best branch based on the Gini coefficient to construct a classification tree. Last, the overall optimal decision tree is generated by means of hyperparameter pruning.

The body shape of middle-aged women in Xinjiang can be divided into three types: standard body, plump body and obese body. The decision tree model has an excellent effect on body classification of middle-aged women in Xinjiang (precision (macro), 95.46%; precision (micro), 95.95%; recall (macro), 95.46%; recall (micro), 95.95%; F1 (macro), 95.46%; F1 (micro), 95.95%).

For scientific research, this paper is conducive to increasing the regional body type theory and stimulating the establishment of a garment sizing subdivision system in Xinjiang. In terms of production practice, this paper not only establishes a model for judging the shape of middle-aged women in Xinjiang, but also provides reference data for intermediates of various sizes. In addition, to facilitate pattern-making and the establishment of a subdivision system for the size of middle-aged women's garments in Xinjiang, this paper provides the grading values of various body control parts of middle-aged women in Xinjiang.

Considering two-dimensional features in the body shape classification system cannot fully reflect the three-dimensional (3D) morphological characteristics of human body. The purpose of this paper is to propose a 3D feature based method to characterize and classify the upper body shape of women, and then obtained the corresponding garment block and improved the fitness of clothing.

In this study, the [TC]² 3D scanner was used to obtain human data, and 15 layers of cross-sections of young females’ upper body were extracted. In total, 240 space vectors were obtained with the center of the bust cross-section as the original point. By using the principal component analysis and K-means clustering analysis, the body shape classification based on the space vectors length was realized. The garment block corresponding to three body types was obtained using the 3D scanning data and the cross-section convex hull, and compared with existing garment block and evaluated fitness of the blocks.

In total, 11 main components used to characterize the 3D morphological features of young women were obtained, which could explain 95.28 percent features of young women’s upper body. By cluster analysis, the body shape of women was divided into three categories. The block of three body types was obtained by the construction of the convex hull model.

This paper investigates a classification method of the body shape based on space vector length, which can effectively reflect the difference of surface shape of human body and further improve the matching degree of human body and clothing.

Identification of human body shapes has been a key issue to develop sizing standards for ready‐to‐wear and to develop made‐to‐measure applications. Current methods to identify the body shapes are mostly based on subjective/visual determination approaches. The purpose of this paper is to look for numerical evaluation parameters for an objective method in order to classify the body shapes and to build up an automated process link.

Female subjects were chosen for the experimental design. 3D body scanning technology was integrated in the process for measurement taking and body silhouette detection of the sample group. Based on this sample data set, body shape identification was realized by referees as visual analyses, and additionally, an objective method was tried out by using body dimensions as numerical evaluation parameters. Obtained results with the sample group were inserted in a database and a body shape calculation tool was developed.

Statistical analyses showed that there is mostly a good agreement between the pairs of the evaluations including the objective calculation methods and the subjective assessments of the referees. The calculation tool was designed as web‐based software in order to integrate with further developments and automation purposes.

A new automatic tool was developed to make the body shape classification objective and repeatable. By integrating this tool to the product development chain, a continuous process link can be provided for the companies through the way for better fitting clothing.

The purpose of this paper is to classify body shapes using angular defects instead of sizes.

A large amount of dimensional data from a national anthropometry survey was analysed, and a basic pattern and its polyhedron were also used to create a three‐dimensional body shape from three body sizes. Using this method, the sizes were converted into nine angular defects.

The authors could define the factors explaining body shape characteristics and classify the body shapes into four groups. The four groups could be characterised by two pattern making difficulties of the upper and lower parts of the body as well as by two proportions, of waist girth to bust girth and bust girth to back length. Furthermore, depending on the age, the authors could understand body shape by the angle made.

Using a polyhedron model, the angles could be calculated using an enormous existing data set of sizes. An angular defect serves as an index to indicate the degree of difficulty for developing a flat pattern. If an angular defect of the bust is large, it is difficult to make a paper pattern of a bust dart. On the other hand, if an angular defect of the waist is large, it is easy to make a paper pattern of a waist dart. Thus, each body shape could be simultaneously characterized by two difficulty indices and two proportions of sizes.

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.

The purpose of this paper is to use body shape analysis and develop a 3D virtual body formation and deformation model that can accurately express size and shape.

In this paper, 1,882 sets of direct measurement data of Korean women in their 20s (19–29 years) were analyzed. These data sets were sourced from the sixth and seventh “Size Korea” anthropometric survey data. Through body shape analysis, the authors classified them into seven body types and selected their representative bodies. A 2D image based on the height, breadth, depth and length was first formed, and the representative virtual body was modeled using the polygon technique. The authors calculated the grading ratios for each body type according to the clothing sizing system, and modified the virtual body size type by morphing technique.

In order to accurately evaluate the fit in a virtual fitting system, it is necessary to study the body size and shape of the target age; this makes it possible to form virtual body reflecting the size and shape.

In this paper, the authors propose a new 3D virtual body formation method that is more accurate in shape and size compared to the present system. Through this, it will be possible to grasp the accurate simulation state in the virtual fitting system, and thereby evaluate the accurate fit.

The purpose of this paper is to derive a new method for developing sizing systems for the mass customization of garments.

A range of recently published works has been studied. A new method is derived by following a basic statistical analysis on anthropometric data which are supported by an iterative mass customization model and introduced “satisfaction performance” indices. The derived method is applied successfully to an anthropometric data consisting of 12,810 Greek men.

With the proposed method, it is possible to control the degree of mass customization and the corresponding number of garment sizes. Under this way, a balance between the number of sizes (in other words: production cost) and the percentage satisfaction of consumers can be achieved. The proposed method consists of six subsequent tasks which are applied to the target population data for the development of mass customization models for male shirts, coats and trousers.

Future work could be focused on the development of methods for the automatic garments grading with respect to the proposed mass customization models and practise.

The methodology presented in this paper can be applied to the development of mass customization models for other categories of garments and target population.

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.

The purpose of this paper is to study how the government stimulates incineration plants to participate in waste classification management, and how to adjust the subsidy strategy for them.

Considering that the classification behavior of residents will produce herd effect, and waste classification can reduce the disposal cost of incineration plants, the authors constructed a differential game model between the government and waste incineration plants, and analyzed the input strategy of the government and incineration plants when they cooperate in the management of municipal waste classification.

Increasing the input level of supervision or raising subsidy price, the government can promote incineration plants to increase the input level of incentive. Moreover, from a long-term perspective, increasing the input level of supervision is more effective. Compared with government supervision, the method of incineration plants incentive can more effectively increase the amount of waste disposal. Furthermore, the government supervision and the incineration plants incentive have a positive interaction effect on improving the amount of waste disposal. Increasing the input level of incineration plants incentive or the level of waste-to-energy technology can increase the amount of waste disposal, and from a long-term perspective, increasing the level of R&D investment is more beneficial to increasing the amount of waste disposal.

The results are helpful to improve the investment in the management of waste classification, and also provide a certain theoretical basis for the government's subsidy policy for incineration plants, so as to reduce the financial pressure of the government.

The purpose of this paper is to develop a virtual body that resembles the customer’s body shape using only the minimum information provided by the customer and without requiring individually scanned data.

The target of this study includes the three-dimensional scanned data of 91 senior women aged 60 or older and human body measurement data of 268 people. The parametric virtual body was generated in three steps: a basic virtual body, a trans-shaped virtual body, and a trans-sized virtual body.

Using organic relationships found in the body shape factors of the lower body, this study developed an algorithm to generate elderly women’s parametric virtual lower body that is quick and reproducible. Having tested the reproducibility of the algorithm, the parametric virtual body showed excellent reproducibility vis-à-vis the personal scanned data in both the shape acceptability and size acceptability.

Because virtual bodies in this study are based on the results of body shape analysis related to apparel design, those resembling customer body shapes can be quickly and accurately generated. In addition, because body shape information for target groups is provided to the clothing manufacturers, it will likely contribute significantly to enhancing clothes fitting.