Improving the Apparel Virtual Size Fitting Prediction under Psychographic Characteristics and 3D Body Measurements Using Artificial Neural Network

3D virtual simulation prototyping software combined with computer-aided manufacturing systems are widely used and are becoming essential in the fashion industry in the earlier stages of the product development process for apparel design. These technologies streamline the garment product fitting procedures, as well as improve the supply chain environmentally, socially, and economically by eliminating large volumes of redundant samples. Issues of non-standardized selection on garment sizing, ease allowance, and size of 3D avatar for creating 3D garments have been addressed by many researchers. Understanding the relationship between body dimensions, ease allowance, and apparel sizes before adopting virtual garment simulation is fundamental for satisfying high customer demands in the apparel industry. However, designers find difficulties providing the appropriate garment fit for customers without fully understanding the motivation and emotions of customers’ fitting preferences in a virtual world. The main purpose of this study is to investigate apparel sizes for virtual fitting, particularly looking at garment ease with consideration of body dimensions and the psychographic characteristics of subjects. In order to develop a virtual garment fitting prediction model, an artificial neural network (ANN) was applied. We recruited 50 subjects between the ages of 18 and 35 years old to conduct 3D body scans and a questionnaire survey for physical and psychological segmentation, as well as fitting preferences evaluation through co-design operations on virtual garment simulation using a commercial software called Optitex. The results from the study demonstrate that ANN is effective in modeling the non-linear relationship between pattern measurements, psychological characteristics, and body measurements. This new approach and the proposed method of virtual garment fitting model prediction on garment sizes using an Artificial Neural Network (ANN) is significant in prediction accuracy. The project also achieves the concept of mass customization and customer orientation and generates new size-fitting data that can bring a new level of end-user satisfaction

Creating garment simulations: Effectiveness of traditional textile testing equipment versus KES and FAST Systems

3D virtual garment simulation software packages offer various fabric alternatives in their fabric libraries. However, these libraries are limited in terms of providing their users with particular fabric compositions, structures, and drape properties. When a specific fabric needs to be used for a garment simulation to understand how the end-product would look like, individual fabric mechanical properties must be entered into the software. For this purpose, usually fabric mechanical values measured by either KES or FAST systems are used. Although these systems provide precise measurements, they are very expensive to obtain. Our research questions emerged from the need to use alternative fabric testing devices to generate outputs to be used in 3D garment simulation software packages. The purpose of this study was to collect preliminary data to investigate if traditional textile testing equipment can be used instead of KES or FAST systems to create garment simulations in Optitex PDS 15

Estimating Cloth Elasticity Parameters From Homogenized Yarn-Level Models

Virtual garment simulation has become increasingly important with applications in garment design and virtual try-on. However, reproducing garments faithfully remains a cumbersome process. We propose an end-to-end method for estimating parameters of shell material models corresponding to real fabrics with minimal priors. Our method determines yarn model properties from information directly obtained from real fabrics, unlike methods that require expensive specialized capture systems. We use an extended homogenization method to match yarn-level and shell-level hyperelastic energies with respect to a range of surface deformations represented by the first and second fundamental forms, including bending along the diagonal to warp and weft directions. We optimize the parameters of a shell deformation model involving uncoupled bending and membrane energies. This allows the simulated model to exhibit nonlinearity and anisotropy seen in real cloth. Finally, we validate our results with quantitative and visual comparisons against real world fabrics through stretch tests and drape experiments. Our homogenized shell models not only capture the characteristics of underlying yarn patterns, but also exhibit distinct behaviors for different yarn materials

Development of information software for automated modeling of women's clothing contours

В статье исследованы технология проектирования и величины параметров моделирования разных видов рельефов плечевой женской одежды. Полученные экспериментальным путем данные дали возможность разработать макрокоманды построения рельефов из линии плеча и проймы в программном обеспечении САПР JULIVI. При использовании макрокоманды построение рельефа и оформление деталей конструкции осуществляются автоматически, конструктор вводит только необходимые величины исходных параметров. Предложено использовать макрокоманды для автоматизированного моделирования одежды, в том числе и в программах 3D проектирования.The article summarizes results of the researches of parameter values of modeling of different types of women`s topwear contours. Experimentally derived data enabled developing macrocommands for contour construction from the shoulder line and armhole for the CAD JULIVI software. Using the macrocommand, contour construction and decoration of the design details are carried out automatically, the designer just sets necessary values of the input parameters. It is proposed to use macrocommands for automated designing of clothing, including 3D CAD programs

3D virtual prototyping of a ski jumpsuit based on a reconstructed body scan model

3D virtual prototyping become a topic of increasing interest of both computer graphics and computer-aided design for apparel production. These technologies are especially important when a garment prototype should be developed for a special purpose, such as ski-jumper suit. Namely, shape and size of a jumpsuit need to be individually adapted to each ski-jumper according to the exact requirements set by FIS (Fédereation Internationale de Ski). The FIS requirements change annually or even more often in order to assure ski-jumpers\u27 safety during competitive ski jumps. The conventional body measurement technique and development of ski-jumpers pattern are time consuming. In order to develop an accurate and rapid design, as well as an adaptable and quickly changeable jumpsuit, different modern technologies were used. The obtained virtual prototypes of a skijumper and a jumpsuit enable both - fast re-modelling according to FIS rules and expeditious development and/or simulations of a jumpsuit. All these measures are taken to improve the aerodynamic design of a suit and jumper\u27s result. The body scanning technology represents a great potential for textile industries and above all for producers of garments. It enables fast and reliable capture of 3D body data and extraction of precise measurements needed for design, construction, visualisation and animation of garments on virtual mannequins. However, there are also some problems related to the scanned body models, caused by the scanning technique. In this article we are discussing the techniques for reconstruction of the body models and its results using the example from one of the competitive sports clothing - ski-jumper suit. In our study we have used different computer graphics programmes in order to reconstruct and prepare the 3D body scan model for successfully importing it into OptiTex CAD programme. The aim of this research was to enable effective 3D virtual garment prototyping using the reconstructed body scan model

Digital 3D reconstruction of historical textile fragment

This paper presents a new methodology for reproducing historic fragment in 3D with realistic behaviour, providing users with a feel for the fragment detailing. The fragment piece originates from the English National Trust archive held in the collection at Claydon House. The aim is to utilize a combination of both 2D pattern software and state-of-the-art 3D technology to recreate a compelling and a highly realistic representation of historic fragment. The process starts with investigation of the textile construction. Textile fragments will be incomplete and/or have a level of deterioration therefore various recording techniques are to be explored. A combination of both photography and 3D scanning technology will be utilized throughout the methodology to accurately record the digital data. The equipment setting will be analyzed in order to produce an accurate working method. This paper forming part of a larger study, will specifically focus on the methodology for recording data from one fragment piece