Virtual Garment Research Articles

Dynamic Mesh Deformation Algorithms for Accurate Virtual Garment Adaptation

Dynamic Mesh Deformation Algorithms for Accurate Virtual Garment Adaptation

The influence of AR virtual clothing design elements on Chinese consumers’ purchase intention: Novelty, craftsmanship, trendiness, and sociability

In the context of the burgeoning digital fashion industry, this study investigates the factors influencing consumer purchase intentions for virtual garments. Through literature review, this study constructed a theoretical model comprising seven latent variables: trendiness, novelty, sociability, craftsmanship, perceived value, perceived quality, and purchase intention, the data of 347 surveys from China are analysed effectively. Results show that novelty, sociability, and craftsmanship not only have a direct positive impact on consumers’ purchase intentions but also indirectly influence purchase intentions through the mediating variables of perceived value and perceived quality. Although trendiness itself did not have a direct significant impact on purchase intention, it could indirectly affect it through perceived value and perceived quality. These insights offer valuable implications for the design and marketing strategies of virtual garment brands, aiming to better align with consumer motives in the digital fashion realm.

Reproducibility of the 3D-Models for Baby and Mother phantom using the platform 3D-Slicer

The evolution of segmentation over the years has offered unlimited potential, with extensive applications in the field of Anatomy. Female pelvis anatomy is reaping great benefits, especially in terms of surgical planning and guidance. Personalize mannequin design are the basic element in virtual garment simulation and visualization and mannequin construction from scanned point cloud and regenerates their shapes by inputting variant dimension., we will describe the segmentation of an existing mannequin and regenerating a new one through 3D Slicer platform, this work is the result of cooperative work between CIGT (Image Guided Therapy Center in the Faculty of Medicine in Nouakchott University-Mauritania) and the IUIBS (Institute for Biomedical and Healthcare Research- University of Las Palmas de Gran Canarias- Spain), involving the segmentation and generation of 3D models for both baby and mother using the 3D Slicer platform.

Estimating Cloth Simulation Parameters From Tag Information and Cusick Drape Test

AbstractIn recent years, the fashion apparel industry has been increasingly employing virtual simulations for the development of new products. The first step in virtual garment simulation involves identifying the optimal simulation parameters that accurately reproduce the drape properties of the actual fabric. Recent techniques advocate for a data‐driven approach, estimating parameters from outcomes of a Cusick drape test. Such methods deviate from standard Cusick drape tests, introducing high‐cost tools, which reduces practicality. Our research presents a more practical model, utilizing 2D silhouette images from the ISO‐standardized Cusick drape test. Notably, while past models have shown limitations in estimating stretching parameters, our novel approach leverages the fabric's tag information including fabric type and fiber composition. Our proposed model functions as a cascaded system: first, it estimates stretching parameters using tag information, then, in the subsequent step, it considers the estimated stretching parameters alongside the fabric sample's Cusick drape test results to determine bending parameters. We validated our model against existing methods and applied it in practical scenarios, showing promising outcomes. (see https://www.acm.org/publications/class-2012)

Correlation between material properties and actual - simulated drape of textile products

With the rapid advancement of digital technology, virtual fashion was born, signifying a milestone in the history of fashion. However, virtual fashion necessitates the accuracy of virtual garments. Therefore, it is necessary to verify that the software accurately reflects the fabric's properties. To accurately evaluate the software, this study altered a few material parameters and compared the results to the actual measured outputs. The selection of three categories of heavy, medium, and light fabrics for measurement is based on industry standards. Sampling based on physical experiments would require a great deal of time and resources; thus, this study proposes a solution to visualize the fabric properties with few inputs in order to surmount the drawbacks of the actual sampling method. The virtual method is utilized to establish fabric properties on the software and assess the drape of various fabric samples. The drape on CLO3D is determined by formatting the fabric's shadow contour, while the drape coefficient is calculated using ImageJ. This coefficient of drapery will be compared to actuality to determine if the software accurately represents the fabric's properties. The drape of the virtual fabric samples after being tried on the virtual mannequin, will be used to design basic garments. Based on the results, the appearance of the product will be evaluated by wearing fabric samples on the virtual mannequin. Increasing the weight of the fabric altered the skirt's appearance due to the higher coefficient of drapery. The increased drape coefficient made the fabric firmer, and the heaviest fabrics were the most rigid, resulting in a greater skirt spread. In contrast, the lightweight fabric exhibited a low coefficient of drape, resulting in softer products. Heavy fabric creates fewer folds. The folds created by the drape of light and medium fabric samples under the effect of their own weight on the CLO3D software are not as smooth and clear as the real samples.

AnMePa: development of a new method for preparing trousers pattern by using the antropometric measurement system

PurposeThis study establishes the principles and process steps of a new basic trousers pattern using measurements obtained according to the rules of the anthropometric measurement system. The newly developed pattern-making system in this study will be called the “Anthropometric Measurements Based Pattern Making System” (AnMePa). It is aimed at producing trousers that are more fitting to the body, thanks to this pattern-making system.Design/methodology/approachIn this research, four pattern-making systems used in many parts of the world were compared with the “Anthropometric Measurements Based Pattern Making System” (AnMePa) with regard to the overall appearance and body fit of trousers prepared according to these systems. 10 virtual mannequins (VM) with different adult female body measurements were created, and trousers patterns were prepared for these mannequins. The trousers’ patterns were made and dressed on the mannequins in a 3D virtual dressing system. The body fit of the virtual garments was evaluated by five experts. The scores given by the experts were evaluated using the fuzzy logic method.FindingsAccording to the results, it is seen that the new basic trousers pattern developed by utilizing the anthropometric measurement system, AnMePa, provides the best body fit among the basic trousers patterns created according to the other examined pattern-making systems. The combination of 3D virtual dressing and fuzzy logic in the evaluation of garment body fit is considered an innovative method for the future of fashion design and production.Originality/valueIn the developed AnMePa, unlike the existing pattern-making systems, values that can be associated with the body measurements of individuals in a way that could be suitable for each community were used instead of constant values in the pattern-making process. Furthermore, the integration of 3D virtual fitting and fuzzy logic in assessing garment fit is considered a pioneering approach with significant implications for the future landscape of fashion design and production.

VR Designer: enhancing fashion showcases through immersive virtual garment fitting

This paper introduces a Virtual Reality (VR) application tailored for fashion designers and retailers, transcending traditional garment design and demonstration boundaries by presenting an immersive digital garment showcase within a captivating VR environment. Simulating a virtual retail store, designers navigate freely, selecting from an array of avatar-garment combinations and exploring garments from diverse perspectives. This immersive experience offers designers a precise representation of the final product’s aesthetics, fit, and functionality on the human body. Our application can be considered as a pre-manufacturing layer, that empowers designers and retailers with a precise understanding of how the actual garment will look and behave. Evaluation involved comprehensive feedback from both professional and undergraduate fashion designers, gathered through usability testing sessions.

Exploring Apparel Design Students’ Willingness to Use Virtual Reality in the Sketching Phase of the Fashion Design Process

Virtual reality (VR) is a computer-generated experience through projection of shapes, objects, and scenic views via headset or helmet device and interpreted as a genuine realistic environment. The interpretation of the highly realistic projection from the eye creates an immersive experience for the user. The use of VR technology is utilized in an array of industry applications as well as learning/training spaces. In particular, when VR is used in an educational setting, studies have shown positive or improved student achievement for a variety of academic disciplines in conjunction with creativity, inspiration, engagement, and motivation. VR used in industry applications, specifically within apparel industries, has been reported to enhance efficiencies in retail, enable virtual garment fitting, and reduction of physical samples in the apparel design and product development process. Regardless of these demonstrated favorable outcomes from education and industry, few research studies have investigated students’ willingness to adopt VR as a tool for use within their desired academic discipline (feeding into their future career path). As use in the apparel design and product development process has been reported, an opportunity exists to explore VR as an educational tool to ideate fashion design ideas in an individual’s apparel design process. Thus, the goal of this study was to provide initial insights into students’ willingness to use VR as a sketching tool, compared to traditional sketching tools, during the apparel design process. A multiple case study design was employed to examine the phenomenon in eight selected undergraduate Apparel Design students. The study was guided through the lens of the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to examine students’ willingness based on performance expectancy, effort expectancy, social influence, and facilitating conditions to use VR. A learning module was developed in a 300-level apparel design course specifically to explore VR as a sketching tool in their design ideation process. Students received a demonstration for how to use the Oculus Quest VR equipment and experimentation/practice time using the equipment in conjunction with the Gravity Sketch (GS) VR application which allowed student users to draw in virtual space on an imported preexisting dress form. Following the practice time, students then completed an apparel design activity using the VR tool. Students then completed a survey in which data was collected through mixed methods by questionary scales and open-ended questions. The findings suggest a relationship between social willingness to adopt VR in their design ideation process while also providing a structure for future researchers to expand the use of this technology in apparel design coursework.

Classification and analysis of fabric types for shirts: A comparison between virtual and real fabrics

The 3D virtual simulation technology is widely applied in the fashion industry tasks, including product planning such as 3D sample work, design development, marketing, and display, enabling styling of virtual models for differentiation. Achieving a digital representation of fabrics that closely resembles actual materials requires additional information obtained through experiments, beyond basic fabric characteristics like fiber content, weight, and thickness. However, research reflecting changes in fabric properties is relatively lacking. Therefore, this study aims to propose criteria for the physical characteristics of shirt fabrics and compare fit variations of virtual garments based on fabric properties to enhance the usability of virtual garment simulation. Thus, we compared and analyzed the characteristics and draping properties of shirt fabrics using two different fabric testing methods, KES-FB and CLO Fabric Kit, and investigated correlations based on each measurement device. Additionally, virtual clothing was performed based on various fabrics to compare clothing suitability. Consequently, we classified fabrics into three clusters for each measurement method and confirmed the characteristics of each cluster. Furthermore, by visually comparing the fit of shirts based on fabric properties, we observed changes in clothing pressure and deformation rate among clusters. Therefore, we believe that the results of this study can assist designers with low proficiency in 3D virtual garment production when applying virtual materials to designs. These findings are expected to be valuable for utilizing 3D virtual clothing simulations in the fashion industry for online sales and marketing, as well as in the gaming industry for avatar costume design.

Investigation on the tension and stretch distributions of textile assembled with seam in virtual garment simulation

Investigation on the tension and stretch distributions of textile assembled with seam in virtual garment simulation

Comparative Analysis of Slacks Pattern for Women with Slim Waists -focusing on 3D virtual garment simulation-

Comparative Analysis of Slacks Pattern for Women with Slim Waists -focusing on 3D virtual garment simulation-

Utilising 3D fashion design software to enable remanufacturing in sportswear

ABSTRACT The boundaries between physical and digital practice within fashion are becoming increasingly blurred, with recent technological advancements seeing brands launching virtual collections and retailing fashion products for the Metaverse. This foray into a digital space has acted as a catalyst for the use of digital software in practical design and make applications and provided opportunities for innovation when challenging ecological parameters. Utilising an action research approach, this paper proposes three cycles of iterative problem solving, creating an interplay between physical and virtual garment experimentation. A process of product deconstruction, digitisation and remanufacture has provided insights into the possibilities of new practices enabling garment remanufacture methods for circularity. Findings have indicated that the use of 3D fashion design software can aid in the diversion of whole garments from the landfill and help enable commercial viability in methods of remanufacture within the sportswear market sector.

Fabric mechanical parameters for 3D cloth simulation in apparel CAD: A systematic review

The primary objective of 3D virtual garment simulation within apparel CAD systems is to generate a highly realistic garment that accurately conform to the human body. However, due to the complexity of textile mechanics, variations in measurement technology, and the absence of standardized units of mechanical parameters, there exists considerable confusion surrounding the implementation of mechanical parameters in cloth simulation. Consequently, the accuracy of cloth simulation varies significantly among different apparel CAD systems. This research article aims to enhance the understanding of the fabric mechanical behaviors, measurement techniques, and parameters essential for cloth simulation. To achieve this objective, we first present a concise overview of current garment simulation in apparel CAD systems, focusing on the utilized mechanical parameters and methods for simulation accuracy evaluation. Subsequently, we delve into the fundamental principles of mechanical behavior, discussing measurement methodologies and proposing parameter unifications along with appropriate data ranges. Finally, we conduct a comprehensive review of cloth models and the requisite parameters, while also exploring simulation-based approaches for parameter estimation. This work provides crucial insights into fabric mechanical parameters essential for achieving accurate 3D virtual garment simulation. The findings and information presented herein can be effectively utilized to enhance the precision and fidelity of apparel CAD systems, thereby facilitating advancements in virtual garment design and production.

Developing of slacks clothing pattern for the elderly men using a 3D virtual garment simulation system

Developing of slacks clothing pattern for the elderly men using a 3D virtual garment simulation system

A novel approach in predicting virtual garment fitting sizes with psychographic characteristics and 3D body measurements using artificial neural network and visualizing fitted bodies using generative adversarial network

Advances in technology have brought accessibility to garment product fitting procedures with a virtual fitting environment and, in due course, improved the supply chain socially, economically, and environmentally. 3D body measurements, garment sizes, and ease allowance are the necessary factors to ensure end-user satisfaction in the apparel industry. However, designers find it challenging to recognize customers’ motivations and emotions towards their preferred fit and define ease allowances in the virtual environment. This study investigates the variations of ease preferences for apparel sizes with body dimensions and psychological orientations by developing a virtual garment fitting prediction model. An artificial neural network (ANN) was employed to develop the model. The ANN model was proved to be effective in predicting ease preferences from two major components. A non-linear relationship was modeled among pattern parameters, body dimensions, and psychographic characteristics. Also, to visualize the fitted bodies, a generative adversarial network (GAN) was applied to generate 3D samples with the predicted pattern parameters from the ANN model. This project promotes mass customization using psychographic orientations and provides the perfect fit to the end users. New size-fitting data is generated for improved ease preference charts, and it enhances end-user satisfaction with garment fit.

The relation between body surface angle and apparel ease distribution under the motion state

PurposeThe purpose of this paper investigates dynamic ease distributions of clothes at bust and waist lines with different body surface angle by using a Qualisys three-dimensional motion capture system (3DMCS).Design/methodology/approachThe current method first obtain the specific markers of participants and their clothes along the bust and waist lines through 3DMCS, then using the least square method and four piecewise polynomial fitting participants and their clothes' bust and waist curves. The coordinates of the markers were tracked by the 3DMCS, while the participants under different body surface angle walked on a treadmill calculated the distances of markers coordinates to the participants' bust and waist curves. Finally, the data of samples were analyzed. It was found that the dynamic ease distributions showed different patterns at different body surface angle.FindingsThe results revealed the bust convex angle is 26.53 degrees (Specification:X3) and back slope angle is 13.96 degrees (Specification: Y1), the fluctuation of participant ease distributions on bust section was most obvious, and the maximum fluctuation value was ±20 mm and ±25 mm. The ease distributions of participant waist section fluctuated most obviously when the bust convex angle is 28.10 degrees (Specification: X5) and the back slope angle is 13.96 degrees (Specification: Y1), and the maximum fluctuation was ±30 mm and ±20 mm. The bust convex angle has the greatest influence on 1# garment, and the back slope angle has the greatest influence on 2# garment.Originality/valueCurrently, there is little information in the literature about dynamic ease distributions of garment on a different body types. This paper takes different body surface angles as the research objects to analyze the ease distributions of different clothes, the conclusion can provide reference data for 3D garment modeling and improve the authenticity of virtual garment fitting.

3D Virtual Garment Simulation and Facial Expression Recognition Technologies, Beauty Filter-based Appealing Self-presentation and Generative Artificial Intelligence Virtual Try-on Tools, and Deep Learning-based Gesture Recognition and Augmented Reality Face Makeup Systems for Body-Image Affective Judgments and Dysfunctional Appearance Beliefs

3D Virtual Garment Simulation and Facial Expression Recognition Technologies, Beauty Filter-based Appealing Self-presentation and Generative Artificial Intelligence Virtual Try-on Tools, and Deep Learning-based Gesture Recognition and Augmented Reality Face Makeup Systems for Body-Image Affective Judgments and Dysfunctional Appearance Beliefs

Clothes with no emperors

Digital garments are tailored computationally and dressed virtually. Intended to be displayed rather than worn, digital fashion exemplifies the function of aesthetic commodities as defined by Gernot Böhme: the production of atmospheres – intangible qualities arising from a material encounter – towards the staging of life. Yet, made from pixels instead of fabric, virtual garments beckon a new conceptual framework for the role of materiality in atmospheric productions. Drawing from new media and affect scholars, this essay traces the display of digital garments across three sites: the e-commerce website, social media, and the runway show. By analyzing the visual and literary production surrounding digital fashion, this essay proposes“elemental surface” as a representational technique and rhetorical strategy through which digital garments produce and intensify the body’s affective presence. Situating Böhme’s formulation of atmosphere in dialogue with the notion of“aura” put forth by Walter Benjamin, the study of digital fashion foregrounds the role of environmental perception in the history of haptic technology.

Retracted: Virtual Garment Piece Design and Stitching Algorithm Based on Virtual Simulation Technology

Retracted: Virtual Garment Piece Design and Stitching Algorithm Based on Virtual Simulation Technology

3D Garment Design Model Based on Convolution Neural Network and Virtual Reality.

The development of virtual reality technology has promoted the unceasing reform and development in the field of fashion design. Aiming at the key technologies and research difficulties in 3D clothing design, the structure of convolution neural network was designed, and a 3D clothing design model based on convolution neural network and virtual reality was constructed. By designing experiments, the average error, matching rate, prediction accuracy, pressure value, and other evaluation indexes are used to measure the performance of convolution neural network model in virtual reality three-dimensional clothing design. The results show that: first, the convolution neural network has the fastest training speed, with the maximum error of 1.63% and the average error of 0.48%. Second, with the increase of parameters, the matching degree of each part of the version and the corresponding data of the human body will gradually increase, the matching rate will slowly improve, and finally tends to 0.9 or so to achieve stability, Thirdly, the prediction accuracy of the convolution neural network is 92.689%, and the loss value is the least. Fourthly, in the virtual fitting and garment wearing experiments, the fit of the sample is within the allowed range, indicating that the automatic generation of fit sample has wearability and rationality.