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The purpose of this paper is to focus on how to automatically generate the individualized patterns for women’s suits based on the 3D body point-cloud images.

With the software Imageware, the point-cloud data of the female body were measured according to the female body feature to obtain the heights, widths, depths and girths at various landmarks. Then the relationship between the height of each landmark and the body height was analyzed to build the height calculation rules by software SPSS, and the prediction models of body girths were established from the body widths and depths using regression analysis for pattern generation.

The pattern generation rules were built with the relationships between a human body and the garment patterns using the graphic flattening method. Based on the above rules, the final patterns were drafted automatically by using these dimensions to fit the subjects. The try-on experiment also showed that the individualized suits could fit the subjects’ body well at some feature landmarks.

In order to realize tailor-made and meet the consumers’ demands for individualized clothes, the development of garment CAD system has become inevitable in the garment industry. This paper could provide the foundation for automatic pattern generation, and technical support for tailor-made.

This study aims to examine the effects of character body size, subject body size and product type on female adolescents’ attitudes toward the character. Given prior research showing that adolescents identify more strongly with those whom they view as similar to themselves, it is possible that heavy and obese adolescents will react more favorably to plus-size ad characters.

Two studies were conducted, one with females aged 12–14 and a second with females aged 15–17. Based on their body mass index, subjects were classified as of small/average size or overweight/obese. Ads featured either a thin, average-size or plus-size character, and promoted either a healthful or an unhealthful snack item.

In general, small/average size female adolescents responded more favorably toward thin characters, whereas their overweight/obese counterparts responded more favorably toward plus-size characters. Moreover, subjects’ responses were not moderated by the nutritional value (healthful vs unhealthful) of the product being advertised.

To effectively promote healthy foods to overweight/obese adolescents, it may be advantageous to incorporate plus-size characters. Additional research is needed, however, to determine whether this approach can effectively influence brand attitudes and consumption behaviors.

As obesity rates continue to rise, it has become vitally important to encourage healthier food choices among youth. To develop effective communication strategies, marketers need to better understand how young consumers respond to various advertising cues.

To the best of the authors’ knowledge, this is the first study to examine the effect of character size and subject size on female adolescents’ attitudes toward the character.

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.

With the rapid advancement of computer information technology, the traditional clothing industry has stridden towards automation and digitization that drive the growth of electronic commerce and line retailing. The purpose of this paper is to propose an approach on 3D upper body modelling based on the body measurements extracted by non-contact anthropometry.

Based on the frontal and side images of the human body, the body sizes were extracted through silhouette extraction, identification of landmarks and girth prediction. The generation rules of 15 characteristic cross-sectional curves were established using a method “feature points – inserted points – feature curves – basic surface – mannequin”. The feature points of each position were determined at each curve, such as the side neck point, front neck point, shoulder point, bust point, and bust root point and so on to get the cross-sections, and then some feature points were inserted at the curves according to the widths and depths to establish the calculative models. For example, there are 18 points distributed at the bust cross-sectional curve to determine the shape.

The final mannequin could describe the basic characteristics of a human body, and the shape of the feature curves could also fit the body type to provide basis for the future research on automatic pattern generation.

This study can realize the 3D virtual modelling of female upper body and the automatic generation of the individualized apparel patterns based on the frontal and side images.

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.

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.

The experiment demonstrated that this method could be used for customized prototype development from 3D body scanning in a relatively easy way.

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.

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.

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.

The research is made in view of the anthropometry information obtaining problem in garment MTM on the network mode. The purpose of this paper is to obtain anthropometry information in a convenient and detailed way in garment MTM on the network mode.

First of all, 24 main measurement sizes of 427 young females are collected to constitute the measurement database. The database is used as background data support of the system. The images are captured to simplify the way of inputting the anthropometry information to the system. Through the 2D feature sizes extracted from body image and the basic dimensions provided by customer input to the system, so that to gain the body sample which is closest to the customer body type through query matching in the database. The detailed anthropometry information of the closest sample is used to describe the customer. The human body measurement database and the technology of body image acquisition are used to extract the feature sizes to achieve obtaining the anthropometry information in a convenient and detailed way.

Through query matching to the customer in a test, the body sample closest to the customer is gained, and the matching error rate is 0.0132. In the end, some customer samples are input to test the system, in order to verify the effectiveness of system functions. The matching error rates of five body types are gained all less than 0.006. The error is small, and the matching result is ideal.

The size of database established in the paper can be increased constantly in the future to obtain the more accurately matching result.

The research of anthropometry information obtaining system in garment MTM on the network mode is the basis to achieve gaining the anthropometry information in a convenient and detailed way.

Applying the established system of human body measurement information acquisition in this paper, it can achieve to obtain the detailed measurement information of customer through a convenient way, combining the method of human body parameter model establishment in the existing research, it can achieve the complete network tailored mode with detailed measurement information acquisition and 3D virtual fitting functions. And it can provide the most convenient experience and the most ideal garment MTM effect to the customer. This mode can be forecast to be an ideal form of garment MTM on the network in the future.

The anthropometry information obtaining system is the important part of garment MTM system on the network mode. It should be applied to the network mode and can obtain the detailed measurements for garment MTM. In this paper, the human body measurement database and the technology of body image acquisition are used in order to extract the feature size to obtain the anthropometry information in a convenient and detailed way.

Repeated exposure to unrealistic notions of female beauty and body shapes, and limited gender stereotypes, may result in the internalization of those standards by pre‐adolescent girls. The purpose of this content analysis is to examine the celebrity role models to whom young girls are exposed via magazines specifically targeted at the “tween” audience. Female celebrities are contrasted with those in magazines targeted at older adolescent girls.

Two pre‐adolescent girls' magazines, Total Girl and Barbie, and two adolescent girls' magazines, Dolly and Girlfriend, were analyzed for the first six months of 2005. All photos (including advertising images) of female celebrities were recorded along with image context; celebrity occupation and age were researched.

Results showed that there was little difference between pre‐adolescent girls' magazines and adolescent magazines in the frequency of celebrity images, and surprisingly only minimal difference in the average age of featured celebrities (22 compared with 23 years old). The occupations of the most frequent celebrities (in all magazines) were limited to actors, singers, and socialites. Further examination of the 12 most frequent celebrities appearing in the pre‐adolescent magazines identified that many of them were publicly recorded as engaging in behaviors such as disordered eating and drug use.

The study is novel in its analysis of celebrities in pre‐adolescent magazines, which have grown in popularity over the last decade. The frequent appearance of relatively older celebrities who could be considered age‐inappropriate role‐models is cause for concern; educational interventions that focus on criticality towards female beauty standards need to be reinforced in primary schools.

The purpose of this paper is to present a method of digital twins of female bodies and the optimization of wetsuit patterns with the help of virtual technologies.

First, the new anthropometrical grouping of female torsos has been developed with 3D body scanning technology. Second, soft tissue deformation under the influence of typical diving postures and hydraulic pressure has been explored. Through real experiments, the relationship between textile material strain and body measurement changing has been applied to establish deformed digital twins of female bodies. Finally, during the evaluation of the virtual wetsuit test on digital twins through material strain and pressure values in CLO 3D, the optimized pattern of the wetsuit has been designed.

The experimental results show that the digital twins based on real data transformation are feasible and practical, and the process of establishing digital twins with 3D body scanning technology is valid and accurate.

The researches on the wetsuit of structure and body dynamic measurements still have many gaps existing in the real and virtual experiments. Thus the manuscript addresses these issues and provides the deformed digital twin for wetsuit pattern design for the first time. This study can be used for designing and optimizing the wetsuit and further improving the efficiency of manufacture and evaluation.

It is suggested that the left hemispheric neurons and the magnocellular visual system are specialized in tasks requiring a relatively small number of large neurons having a fast reaction time due to a high firing rate or many dendritic synapses of the same neuron which are activated simultaneously. On the other hand the right hemispheric neurons and the neurons of the parvocellular visual system are specialized in tasks requiring a relatively larger number of short term memory (STM) Hebbian engrams (neural networks). This larger number of engrams is achieved by a combination of two strategies. The first is evolving a larger number of neurons, which may be smaller and have a lower firing rate. The second is evolving longer and more branching axons and thus producing more engrams, including engrams comprising neurons located at cortical areas distant from each other. This model explains why verbal functions of the brain are related to the left hemisphere, and the division of semantic tasks between the left hemisphere and the right one. This explanation is extended to other cognitive functions like visual search, ontological cognition, the detection of temporal order, and the dual cognitive interpretation of the perceived physical phenomena.

This study seeks to determine if body image disturbance and eating disorders that have plagued Western women are now becoming more common in Asia as well. Additionally, it attempts to examine perceptions of the impact of models in advertising in both cultures. The third person effect which states that people believe the media impacts others more than themselves is tested to determine if this contributes to behaviors related to body image. A comparison of responses from young women inHong Kong and the US indicate that both cultures are similar in the degree of body dissatisfaction and dieting behavior exhibited. However, Western women spend significantly more time exercising and are more willing to have plastic surgery to improve their appearance. The third person effect appears robust across cultures, but generally does not contribute significantly to explaining body image related attitudes and behaviors. The results have important implications for both third person effect and cross cultural consumer behavior.