Cloth Model Research Articles

The GENERATION Z CONSUMER BEHAVIOR TOWARDS LOCAL AND IMPORTED FASHION PRODUCTS

Indonesia's domestic market, which is a very broad market with a very dense total population which can be estimated at around 270 million people (BPS, 2021). Such a large domestic market can push the possibility of forming a strong competition or competition between imported products and local products. Increasing local brands is a strategic step that is useful to show or introduce Indonesian-made products to the global market. The purpose of this research is to understand the attitudes of Generation Z consumers towards local and imported fashion brands.
 The research methodology uses a descriptive qualitative approach. Data collection using questionnaires can be explained according to student behavior on the use of local fashion brands and imported fashion.
 In Generation Z, both men and women, do not tend to buy imported fashion products, do not tend to buy the latest imported brand brand clothes, do not agree to buy different imported brand products with the same quality and lack confidence in wearing imported fashion brand clothes, but like to buy product clothes quality imports.
 With the quality of the product, it can be the first benchmark in product evaluation and this also depends on the attitude of the consumer. The results of the study explain that Generation Z men and women, tend to buy local fashion products, tend to buy the latest local brand clothing models, like to buy quality local clothes, often buy different local brand products but the quality is the same and are more confident by wearing fashion clothes. local brands.
 So it can be concluded that most of Generation Z are more likely to buy local brand fashion products. And for the quality of local products, you can say that they are not far behind imported products, so it can be said that local products can compete with imported products.

Progressive Simulation for Cloth Quasistatics

The trade-off between speed and fidelity in cloth simulation is a fundamental computational problem in computer graphics and computational design. Coarse cloth models provide the interactive performance required by designers, but they can not be simulated at higher resolutions ("up-resed") without introducing simulation artifacts and/or unpredicted outcomes, such as different folds, wrinkles and drapes. But how can a coarse simulation predict the result of an unconstrained, high-resolution simulation that has not yet been run? We propose Progressive Cloth Simulation (PCS), a new forward simulation method for efficient preview of cloth quasistatics on exceedingly coarse triangle meshes with consistent and progressive improvement over a hierarchy of increasingly higher-resolution models. PCS provides an efficient coarse previewing simulation method that predicts the coarse-scale folds and wrinkles that will be generated by a corresponding converged, high-fidelity C-IPC simulation of the cloth drape's equilibrium. For each preview PCS can generate an increasing-resolution sequence of consistent models that progress towards this converged solution. This successive improvement can then be interrupted at any point, for example, whenever design parameters are updated. PCS then ensures feasibility at all resolutions, so that predicted solutions remain intersection-free and capture the complex folding and buckling behaviors of frictionally contacting cloth.

A multi-segmented human bioheat model under immersed conditions

A multi-segmented human bioheat model was developed to characterize the heat exchange phenomena of the human body while immersed in water and to predict the body's thermoregulation and physiological reactions under immersed conditions. The model is based on the Tanabe model, which divides the human body into 15 segments according to the “Walter” thermal manikin. Each segment is made up of the core layer, muscle layer, fat layer, skin layer and central blood layer. The wet clothing model, which uses empirical equations derived from several underwater manikin experiments, is used in the multi-segmented human bioheat model to represent the mechanism of heat exchange between the human body and the outside world through wet clothing after falling into water. Ten healthy males were chosen for the water immersion experiment and placed in a climatic chamber with simulated falling water. Six different body parts' core temperatures, skin temperatures, and heat flow densities were continually monitored throughout the experiment. By contrasting the experimental results of the water immersion environment with the multi-segmented human bioheat model's predicted outcomes, the accuracy of the model was assessed. The results showed that the values predicted by the model simulation matched the results of the experiments, which indicates that the multi-segmented human bioheat model was reliable, valid, and very useful.

Pattern-Based Cloth Registration and Sparse-View Animation

We propose a novel multi-view camera pipeline for the reconstruction and registration of dynamic clothing. Our proposed method relies on a specifically designed pattern that allows for precise video tracking in each camera view. We triangulate the tracked points and register the cloth surface in a fine-grained geometric resolution and low localization error. Compared to state-of-the-art methods, our registration exhibits stable correspondence, tracking the same points on the deforming cloth surface along the temporal sequence. As an application, we demonstrate how the use of our registration pipeline greatly improves state-of-the-art pose-based drivable cloth models. Furthermore, we propose a novel model, Garment Avatar , for driving cloth from a dense tracking signal which is obtained from two opposing camera views. The method produces realistic reconstructions which are faithful to the actual geometry of the deforming cloth. In this setting, the user wears a garment with our custom pattern which enables our driving model to reconstruct the geometry. Our code and data are available at https://github.com/HalimiOshri/Pattern-Based-Cloth-Registration-and-Sparse-View-Animation. The released data includes our pattern and registered mesh sequences containing four different subjects and 15k frames in total.

Robust and automatic clothing reconstruction based on a single RGB image

We propose a novel method to reconstruct style-matched and texture-realistic clothing from a single image. Our work mainly addresses two challenging problems in clothing reconstruction: (1) how to automatically generate style-consistent geometric clothing models from a single image; (2) how to generate realistic clothing texture when suffering from significant pose estimation error. For the former (geometry reconstruction), we propose a coarse-to-fine approach to empower TailorNet to process image inputs and generate style-matched clothing. The key is that our two-stage method can predict clothing style parameters (TailorNet’s latent vectors indicating clothing shape) from images. We first use an attribute prediction network to identify the gender, clothing type, and style categories from the input. Then, we propose a tightness table-based estimation method to obtain specific clothing style parameter values. For the latter (textures generation), we design a multi-information fusion approach to deal with ghosting issue caused by pose estimate errors. The method utilizes semantic and intrinsic texture information to effectively deal with wrong color sampling in the image. Extensive experiments demonstrate that our method has reached the state-of-the-art level and realized the realistic body and clothing reconstruction from a single RGB image.

Review of cloth modeling and simulation for virtual fitting

Virtual fitting technology is widely used in many fields, such as e-commerce, garment computer-aided design, and film and game production. Cloth modeling and simulation play an important role in virtual fitting. The realism and simulation speed directly affect the user experience and visual appearance. This paper first reviews the history of cloth modeling and simulation methods. Then, it focuses on four perspectives: yarn-structure modeling of the cloth modeling level; multi-resolution grid simulation; the relation between human posture and cloth deformation; and collision problems of the cloth simulation level. Yarn-structure modeling considers a unit cell that incorporates the physical characteristics of the fabric and the fabric structure. A multi-resolution grid can integrate techniques from different research fields and may achieve a breakthrough in cloth modeling. Generative adversarial networks (GANs) have potential for dealing with the relation between human posture and cloth deformation by comparing several typical algorithms with GANs. Solving the collision and friction problem depends on choosing the right envelope box for refining the human body surface. Finally, the paper concludes with an analysis of future research trends that could improve the fidelity and speed of a simulation. The paper may serve as a reference for research into cloth modeling and simulation for virtual fitting.

ARTISTIC AND COMPOSITIONAL FEATURES OF CHILDREN'S COSTUME IN UKRAINE OF THE 20th – EARLY 21st CENTURIES

Purpose. The study of artistic imagery of children's costume by Ukrainian fashion designers of the 20th – early 21st centuries, establishment of features and patterns in the repetition of artistic and compositional solutions of children's costume, identification of established trends and innovations in the decoration of children's clothing.
 Methodology. Visual-analytical method, morphological, artistic-compositional and retrospective analysis were applied.
 Results. As a result of the analysis of children's clothing models of Ukrainian designers and brands, the artistic and compositional features of children's costumes and current trends in the decoration of children's clothing of the 20th – early 21st centuries are identified. It is determined that during this period, possibilities for the implementation of artistic imagery of clothing for children have expanded due to innovative materials and decoration technologies, but even in our time, traditional types of decoration that have been characteristic of children's costumes for centuries do not lose their relevance.
 The scientific novelty of the research consists in identifying features of artistic and figurative solutions of children's clothing by designers of Ukrainian fashion houses and leading trends in the decoration of children's costumes in Ukraine of the 20th – early 21st centuries.
 Practical significance. The collected materials and their analysis allowed to summarize information about artistic solutions and children's costumes by designers of Ukrainian fashion houses, which can serve as a basis for further research on the history of fashion and children's clothing design, information base for creating new collections of children's clothing.

Zapożyczenia z języka angielskiego w polskich i chorwackich nazwach spodni

The changes taking place in the fashion industry related to the overproduction of clothing, consumerism and globalisation result in the introduction of new clothing models on the market, and thus the creation of new names for individual styles. English is currently the lingua franca in the fashion world, which means that the number of loanwords from this language in other languages is increasing. The aim of this work is to record, categorise and compare English loanwords used as the names of trousers appearing in Polish and Croatian versions of clothing online stores. The analysis consists of indicating the English name of the model, checking the presence of individual lexemes in the dictionaries of the given language and determining the types of borrowing adaptations. The article ends with comparative conclusions.

Application of convolution neural networks‐based hierarchical perception technology in 3D clothing designs

The purpose of this research is to solve the problems in the modern life, such as the inconvenience caused by fast life pace, the need to save time, the unsatisfactory products for consumers, the low brand awareness in the clothing industry, serious product homogenisation and low life quality. The study of the application of hierarchical perception technology in 3D (three-dimensional) clothing designs is carried out based on CNN (convolutional neural networks). The study includes the training of CNN, the selection of 3D clothing models and 2D (two-dimensional) projection of 3D human body models. A simulation experiment is conducted by taking 49-year-old males, 22-year-old males and 50-year-old females as research objects. The findings show that the training network can effectively identify the typical lines of the human's hindneck, chest, shoulders, and waist, and the accuracy of the front and side recognition of the human body can be reached as high as 93% on average. The effective identification of human characteristics is achieved. The study has an important impact on the technical field and clothing industry and also has profound theoretical and practical significance.

Modelling and experimental study of thermo-physiological responses of human exercising in cold environments

A numerical human thermo-physiological model is developed with the consideration of characteristics of exercising people in cold environments. The developed model is characterized by: 1) the concept of net exercise efficiency which is used to correct the calculation of metabolic heat production by excluding mechanical energy; 2) the effects of low temperature on basal metabolic rate and basal blood flow rate; 3) the integration with a multi-layer clothing model to calculate the heat and moisture transfer through the clothing system, which takes into account the air gaps between the clothing layers to reflect the ventilation and air penetration effect from the ambient wind. Human subject experiment is conducted in a climate chamber to validate the proposed model. The human subject experiment is also carried out in a cold environment (−5 °C) combined with different air velocity conditions (still air, 2 m/s), taking into account the activities of different intensities (standing statically, 2 km/h walking and 7 km/h running). Thermo-physiological parameters including the core temperature, 8-point local skin temperatures and the clothing layer temperatures, are measured during the experiment. Comparison between the predicted and experimental results gives the root mean squared error (RMSE) of core temperature and mean skin temperature of 0.06–0.10 °C and 0.17–0.27 °C, respectively. RMSE values for local skin and clothing layer temperatures are no higher than 1.5 °C and most within 0.8 °C. The model is also validated with published data under various ambient temperature and activity intensity conditions. The proposed model is shown to be capable of predict the thermo-physiological responses of people exposed and exercising in cold environments.

Geometry image super-resolution with AnisoCBConvNet architecture for efficient cloth modeling.

We propose an anisotropic constrained-boundary convolutional neural networks (hereafter, AnisoCBConvNet) that can stably express high-quality meshes without oscillation by applying super-resolution operations to low-resolution cloth meshes. As a training set for the neural network, we use a pair between simulation data of low resolution (LR) cloth and data obtained by applying the same simulation to high resolution (HR) cloth with increased quad mesh resolution of LR cloth. The actual data used for training are 2D geometry images converted from 3D meshes. The proposed AnisoCBConvNet is used to train an image synthesizer that converts LR geometry images to HR geometry images. In particular, by controlling the weights anisotropically near the boundary, the problem of surface wrinkling caused by oscillation is alleviated. When the HR geometry image obtained through AnisoCBConvNet is converted back to the HR cloth mesh, details including wrinkles are expressed better than the input cloth mesh. In addition, our results improved the noise problem in the existing geometry image approach. We tested AnisoCBConvNet-based super-resolution in various simulation scenarios, and confirmed stable and efficient performance in most of the results. By using our method, it will be possible to effectively produce CG VFX created using high-quality cloth simulation in games and movies.

COLOR-INFORMATION TECHNOLOGIES AS A COMPONENT OF BRAND-COLORISTIC OF SEWING PRODUCTS

The article is devoted to solving the task of analyzing the essence, features, and rules of brand coloristic as a tool for influencing the target audience of a fashion brand. The authors proposed approaches to using mobile applications as color information technologies to develop brand coloristic of the projected image of a clothing model. As a result of the conducted research, a color design strategy for fashion brand garments was developed. The essence of a comprehensive study of color perception: its theory and practice, personalities, institutions, semantics, and the use of color information technologies for developing brand coloristic of the projected image of a clothing model is substantiated. The interaction of color in art, design, advertising, and science has been proven. Based on consumers’ physiological, emotional, intellectual, and behavioral reactions to color, a comprehensive system, “The meaning of color,” is proposed. The motives and behavioral mechanisms of consumers in the fashion industry have been studied, and the factors affecting the purchase decision have been determined. This made it possible to represent the information model of the reaction to the garment, as a component of the clothing color design strategy, by including subsets of stimuli and emotions in the design-projection process. The main rules of modern brand coloristic were analyzed and applied using modern color information technologies in the form of a ready-made Color Gear mobile application. The proposed process of using current color and information technologies to harmonize the graphic fashion image allows you to get an individual coordinated project image with a planned impression. Thus, it has been proven that the elements of brand color are an essential factor that affects the consumer’s perception of fashion brands and, as a result, sales and profits. Broad prospects for further development of the author’s mobile application for harmonizing clothing colors have been revealed, especially when it comes to finding a new color project image because the competition of fashion brands is active and demanding at the current stage.

INNOVATIVE TECHNOLOGIES FOR DECORATING LIGHT INDUSTRY PRODUCTS

The article is devoted to the solution of the task of forming project images in modern mass fashion in the context of the use of innovative decoration technologies on the example of designing an author’s collection of women’s clothing. The scientific novelty of the study consists of the analysis and systematization of creative and innovative decoration technologies with the aim of further integration into the fashion design of clothing. The study’s practical significance lies in the study of characteristic techniques and elements of innovative clothing decoration. The article describes the stages and provides recommendations for producing the author’s prints for decorating products of the author’s collection. The authors focused on developing the author’s print using computer technologies in universal graphic reactors of both raster and vector graphics for further thermal transfer printing. The study demonstrates the process of forming a sketch of a fashionable design image using an information model, which allows authors to present it as a single symbolic system using modern practices of visual presentation of trendy innovations. The products in the collection are made of different materials, which, when combined into sets, give the image of unusualness and sophistication. The collection was developed in the format of the Pop Art style using fashion trends. The authors defined and thought out the main images, forms, and constituent elements of the designed products of the author’s collection sets. When creating clothing models, special attention was paid to the originality and multifunctionality of the collection’s products and their parts. The creative and design, constructive, and technological solutions of models of sets of the author’s collection were produced and presented at the All-Ukrainian competition of young designers “Colours of Podillia” (Khmelnytskyi, KhNU, 2022), were developed.

Pengaruh Promosi Dan Brand Ambasador Terhadap Keputusan Pembelian Sepatu Pada PT. Sepatu Bata Tbk. Cabang Karawang

In the current era and the increasing market demand in the fashion industry, the world is currently increasingly aggressively developing clothing models that are in line with current developments. The purpose of this study was to determine the effect of promotion and brand ambassadors on purchasing decisions at PT. Shoes Bata Tbk. Karawang Branch. The sample in this study is as many as 100 respondents from customers Shoes Bata Karawang Branch. This research uses the descriptive verification method. The sampling technique used in this study was disproportionate stratified random in determining the number of samples using the Slovin formula with an error rate of 10%. The type of data used in this study is to use secondary and primary data. The data analysis technique used is simple linear regression. The results of this study indicate that promotions and brand ambassadors influence purchasing decisions.

An individualized thermoregulatory model for calculating human body thermal response in chemical protective clothing

Human thermoregulatory models could be used to assess body temperature and thermal stress in chemical protective clothing. Most models in the literature were exploited based on military standard geometry and without consideration of anthropometric differences in the human body and intensity of exercise during combat tasks in different environments and were seldom applied in chemical protective scenarios. This study aims to develop a thermoregulatory model containing the passive and active systems. The passive system defines human body geometry and tissue physical properties and simulates bio-heat transfer in each segment and between the skin surface and surroundings, while the active system simulates the regulation of metabolism, respiration, circulation and sweating. The heat transfer between two adjacent segments was calculated from blood circulation. The boundary conditions include convection, radiation and evaporation on human skin with or without non-uniform clothing. This study evaluated the model's performance for subjects with basic combat clothing and chemical protective clothing under neutral and adverse thermal environmental conditions. Comparisons with experimental data indicate that the present model is suitable for simulating human thermal responses when exposed to two kinds of ambient temperatures with exercise tasks. Results from the present model were acceptable in the prediction of core and local skin temperature, and the accuracy of the thermoregulatory model for core and skin temperatures could be improved via optimization of specific characteristics of the human body, chemical protective clothing model and the continuous change of physiology under dynamic conditions.

The Progress of Business Analytics and Knowledge Management for Enterprise Performance Using Artificial Intelligence and Man-Machine Coordination

This study aims to explore the integration of human-computer interaction (HCI) technology and platform ecosystem in artificial intelligence (AI) environment, thus providing a practical basis for the intelligent development of strategic management of platform ecosystem. With clothing e-commerce as an example, first, the business model of brand clothing is simply analyzed. Then, the fashion knowledge management method is adopted to build the fashion data warehouse. The platform intelligent clothing ecosystem is innovatively put forward through the research of business analytics and management mode of clothing e-commerce industry. The optimized genetic algorithm is used to solve the objective function of the model, and a flexible production scheduling model with multiple constraints and maximum cost-saving is established. Finally, the questionnaire results of voice interaction users are analyzed by HCI customer trust model.

Image-based virtual try-on system with clothing extraction module that adapts to any posture

In this study, we developed a virtual try-on system that automatically creates a clothing model from a person’s image, and thus a clothing model is not required as an input. Recently, the scale of the E-commerce market in the fashion field has expanded. When purchasing clothes on a fashion E-commerce site, a user can browse and buy various brands at once without visiting a physical store. However, users cannot pick up the actual clothes and try them on. Therefore, the user may not be satisfied with the design and size after receiving clothing bought on-line. Virtual try-on systems have been developed in various studies that allow users to virtually try on clothes using a computer. In particular, many image-based virtual try-on systems have been reported that transition the clothing model’s features to the clothing area on the target person. However, this method has the following problems: (1) it is necessary to prepare a clothing model in advance and (2) the posture for changing clothes is restricted. Thus, we developed a virtual try-on system that does not require a clothing model as an input, thereby enabling the automatic creation of a clothing model from a person’s image by incorporating a clothing extraction module into the virtual try-on system. In addition, we improved the virtual try-on system so it can adapt to any posture and evaluated the improvements in simulations.

Business Plan Clothing Business “The X Aksha” in Bali

This research aims to evaluate all aspects of the business viability of the clothing business "The X Aksha". With the increasingly rampant competition in Indonesia, especially in terms of dress. Here "The x Aksha" offers summer casual style-themed clothing designs with good quality and affordable prices. The purpose of establishing "The x Aksha" is to provide several models of clothing that are environmentally friendly and comfortable to use during this pandemic with attractive designs and affordable prices. From the results of calculations on the financial aspect for 5 years, the NPV is Rp. 1,198,996,338 and the IRR is 68%, where the payback period is 1 year 2 months, so from these results it can be concluded that this clothing business project is feasible to run.

The predicted heat strain model considering wet and dynamic thermal insulation for thermal protective clothing: Modification and validation analysis

For guiding the setting of working time, it is necessary to develop a realistic clothing model with accurate thermal physical properties including the effects of human body activities and environments in the predicted heat strain model, especially for the high thermal insulation clothing ensembles and high-temperature conditions. In this study, realistic clothing models, including clothing wet thermal insulation ( Icl_w), dynamic thermal insulation ( Icl_vw), and convective heat transfer coefficient considering the temperature difference and walking speed ( hc_vw), were established. Then, we validated the modified predicted heat strain models combined with realistic clothing parameters. The results revealed that the core temperature of the predicted heat strain model combined with Icl_w, Icl_vw, and hc_vw (deviation of 0.1°C) was significantly more accurate than the original predicted heat strain model (variation of 1.5°C) in the environment of 40°C within 65 min of heat exposure. Our study emphasizes the necessity of ensuring the accuracy of clothing thermal physical properties in the predicted heat strain model to improve validity for the specific conditions investigated.

Construction of Knowledge Graph of 3D Clothing Design Resources Based on Multimodal Clustering Network.

The construction of 3D design model is a hotspot of applied research in the fields of clothing functional design system teaching and display. The simple 3D clothing visualization postprocessing lacks interactive functions, which is a hot issue that needs to be solved urgently at present. Based on analyzing the existing clothing modeling technology, template technology, and fusion technology, and based on the multimodal clustering network theory, this paper proposes a 3D clothing design resource knowledge graph modeling method with multiple fusion of features and templates. The position of each joint point is converted into the coordinate system centered on the torso point in advance and normalized to avoid the problem that the relative position of the camera and the collector cannot be determined, and the shape of different collectors is different. The paper provides a multimodal clustering network intelligence method, illustrates the interoperability of users switching between different design networks in the seamless connection movement, and combines the hybrid intelligence algorithm with the fuzzy logic interpretation algorithm to solve the problems in the field of 3D clothing design service quality. During the simulation process, the research scheme builds a logical multimodal clustering network framework, which integrates compatibility access and global access partition fusion of style templates to achieve information extraction of clothing parts. The experimental results show that the realistic 3D clothing modeling can be achieved by layering the 3D clothing map, contour features, clothing size features, and color texture features with the modeling template. The developed ActiveX control is mounted on MSN, and the system is compatible. The performance and integration rate reached 77.1% and 89.7%, respectively, which effectively strengthened the practical role of the 3D clothing design system.