Virtual Clothing Research Articles

Digital Twin-Based Alternate Ego Modeling and Simulation: Eva Herzigová as a 3D MetaHuman Avatar

Abstract Due to Dimension Studios and Unsigned Group, by likeness and movement digitization, the human supermodel Eva Herzigová’s highly realistic metahuman and 3D digital twin lead to perpetual career extension (e.g., on virtual runway shows by catwalk replication or in advertising campaigns by particular pose adoption), including in virtual worlds such as metaverse spaces, by use of extended reality technologies, in terms of virtual clothing, digital hair, skin texture, facial and body expressions, and makeup styling as avatar appearance and persona. In this paper, we show how, by likeness capturing (e.g., signature walk by motion capture shoot for face and body movement tracking) and virtual clothing, Eva Herzigová’s hyperreal 3D avatar (lifelike 3D digital human clone or realistic virtual human) is configured with subsequent restyled hair and make-up, 3D clothing modeling, and extended reality fashion shows on virtual catwalks or campaign shoots. We clarify that photographic reference materials and a sensor-based motion capture suit assisted Metahuman Creator in capturing facial and motion data for Eva Herzigová’s digital avatar, configuring realistic depiction and virtual activations of beauty standards, in addition to digital likeness, signature style, talent representation, and narrations, typifying digital human creation and presence in virtual worlds (e.g., for metaverse-based shoots). We conclude that Eva Herzigová’s hyperrealistic 3D digital human twin and MetaHuman avatar operate as a styled virtual alter ego and versatile personal brand extension by motion capture technologies for immersive virtual fashion shows, live video streams and broadcast, and digital wearable modeling.

A Comprehensive Approach to Pattern Drafting for Women with Large Bust Cup Sizes through Advanced 3D Virtual Clothing Systems

A Comprehensive Approach to Pattern Drafting for Women with Large Bust Cup Sizes through Advanced 3D Virtual Clothing Systems

Modeling of virtual clothing and its contact with the human body

Abstract Aiming to tackle the issue of virtual fitting, this study proposes an integrated solution encompassing key stages, such as fabric modeling, virtual stitching algorithms, and clothing–body contact mechanisms, with focus on simulating and calculating the clothing pressure. A fabric model based on a particle–spring system is developed, with an emphasis on exploring the relationship between spring coefficients to achieve parametric independence of the virtual fabric. To turn the fabric into clothes, an algorithm for stitch line generation is introduced along with discussions on springs with constraint to improve the rendering accuracy and enhance effects. For simulating the clothing–body contact, a body characterization model consisting of slices is constructed and utilized to compute fabric deformation and its pressure exerted on the human body. Validation tests are conducted by comparing calculated pressures with real measurements obtained from a mannequin, demonstrating an error of 10.9% for the fit size of clothing and below 10% for smaller sizes. These results indicate that the proposed solution not only enables realistic visual effects of virtual clothing but also generates meaningful pressure values based on fabric properties, clothing patterns, and sizes. This lays a solid foundation for the valuable assessment and prediction of clothing pressure in virtual fitting scenarios.

Advances in personalized modelling and virtual display of ethnic clothing for intelligent customization

Abstract To enhance the intelligence of the ethnic clothing customization industry and provide online solutions for clothing ordering and fashion shows, this study analyses the latest developments in the fields of digital human models, 3D clothing models, and virtual clothing displays in recent years. This study focuses on analysing the categories and processes of three related technologies in clothing virtual display and compares the advantages and disadvantages of four human body modelling methods. Reshaping the facial features of a 3D body scan model and binding the bones of each part is key to providing a personalized body model. In addition, 3D clothing modelling technology is classified into three methods. The 3D fabric scan data are used to establish realistic seam information and process details simulation and use hybrid modelling methods to virtually sew 2D samples, which can enhance the realism of clothing models. The virtual display platform for ethnic clothing is constructed through layered design based on the Unity3D engine, matching versions and virtual display. The above research ideas can solve bottleneck problems in clothing customization. This has important guiding significance for opening up the ethnic clothing customization market, promoting the intelligence of the customization industry, and promoting ethnic clothing culture.

Disassembling the components of virtual clothing presentation: exploring their impact on consumers' perception and purchase intention

PurposeVirtual clothing presentation has a visual 3D effort and allows consumers to interact. Currently, most scholars make virtual clothing presentations as a whole or focus on one element to study its impact on consumers’ purchase intentions. This study disassembles the components of virtual clothing presentation in Taobao and explores how each component (virtual clothing, virtual model, presentation space, presentation technology and system quality) affects consumers’ purchase intention, which can provide clothing companies recommendations for developing it and help improve consumers’ online shopping experience.Design/methodology/approachThis study created the parts of a virtual clothing presentation and took advantage of Taobao’s 3D interactive module to simulate a shopping scenario. Participants experienced a 3D interactive virtual clothing presentation in which they could change clothing colors, show actual clothing sizes, try different model poses, switch presentation backgrounds and unfold clothing structure through interactive buttons. Then they were randomly assigned to view two kinds of images and videos of experiment clothing (real images and videos vs virtual ones), respectively. Hypotheses were tested using SEM and applying SmartPLS 4.FindingsThe results demonstrated that five components of virtual clothing presentation have different degrees of influence on consumers’ purchase intention through different consumer perceptions (perceived usefulness, ease of use and enjoyment). It is necessary to consider the design of the virtual clothing presentation in those five dimensions for different needs. In addition, it is feasible to replace images and animated videos of real clothing with virtual ones in Taobao.Originality/valueDifferent types of virtual clothing presentations can lead to various results in terms of diverse impacts. This study disassembles and researches each component of a virtual clothing presentation. Overall, this study could provide guidance and suggestions for clothing companies to develop and design or invest in virtual clothing presentations.

Exploring Virtual Fashion Consumption through the Emotional Three-Level Theory: Reflections on Sustainable Consumer Behavior

The fast fashion industry has been widely criticized for its substantial consumption of resources and significant environmental pollution. In contrast, virtual fashion clothes are attracting attention from consumers and academics for their notable sustainability benefits and potential for fashion innovation. However, research on consumer acceptance of virtual clothes and the role of sustainability remains limited. This study aims to fill this gap by applying the Emotional Three-Level Theory to identify key virtual fashion attributes, including aesthetic, reality, personalization, presentation, sustainability, and inclusivity features, and evaluating their impact on acceptance using the Technology Acceptance Model (TAM). A survey of 503 Generation Z consumers in China, analyzed through structural equation modeling, reveals that perceived enjoyment, usefulness, and ease of use significantly influence the intention to adopt virtual fashion clothes. Aesthetic and realistic features enhance enjoyment, while personalization and presentation improve usefulness and ease of use. Sustainability features positively impact all three factors, promoting consumer acceptance. These findings offer theoretical insights for virtual fashion research and practical guidance for the fashion industry to leverage virtual technologies for environmental sustainability. Notably, the study emphasizes the potential of virtual clothes in promoting sustainable development in the fashion industry.

3D 의류 시뮬레이션 Z-weave 프로그램을 이용한 실물 소재 비교와 지속 가능한 패션 산업에서의 실현성

This study aims not only to address environmental issues caused by indiscriminate fashion consumption, specifically in the context of Fast Fashion but also to find an alternative and a sustainable solution that is ‘Upcycling’ using the 3D clothing simulation program Z-weave. Upcycling products have limitations in that it is difficult to produce samples since finished products must be produced directly with limited materials and resources like waste clothes. To overcome these limitations, a 3D clothing simulation program is introduced to effectively utilize the limited resources of waste clothing. The purpose of this study is to confirm the similarity between a virtual fabric created through Z-weave and a real fabric, through this, to evaluate the possibility of application in the actual fashion industry. As a research method, surveys and interviews were conducted with related majors on virtual clothing created as similar as possible to actual clothing by adjusting the physical properties within the Z-weave program. This study attempted to describe the impact of digital technology on the fashion industry and how 3D clothing simulation programs can be used in sustainable fashion production.

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.

The Influence of Interactivity, Aesthetic, Creativity and Vividness on Consumer Purchase of Virtual Clothing: The Mediating Effect of Satisfaction and Flow

With the rapid global growth of digital fashion, virtual clothing has recently become a hot research topic. However, there is still little literature exploring the mutual influence between virtual clothing design features and consumer purchase intentions. This study delves into the dynamic relationship between virtual clothing design attributes and consumer purchase tendencies, seeking to foster a balanced development of the virtual clothing industry. Following a literature review, this study formulated a theoretical model that includes seven key latent factors: Interactivity, Aesthetic, Creativity, Vividness, Satisfaction, Flow experience, and Purchase Intention. Anchored in the Stimulus-Organism-Response (SOR) paradigm, the study conducted offline trials where respondents tried on virtual clothing using AR as a stimulus, carefully examining data from 295 respondents. The analysis shows that while Interactivity and Aesthetics significantly increase the likelihood of consumer purchases, Creativity and Vividness lack a direct and substantial impact on this intent. Satisfaction and Flow experience are important mediating variables that profoundly influence the purchasing decisions for virtual clothing. The findings of this study provide new insights into virtual clothing design and marketing strategies, emphasizing the importance of optimizing user interaction and Aesthetic experiences in enhancing consumer purchase intentions.

Digital Virtual Simulation for Cultural Clothing Restoration: Case Study of Tang Dynasty Mural ‘Diplomatic Envoys’ from Crown Prince Zhang Huai’s Tomb

The advent of 3D virtual presentation technology for clothing has led to the gradual popularisation of digital virtual clothing in the modern fashion industry. However, there remains a gap between the application of this technology and the integration of cultural attributes in the field of digital communication of traditional cultural clothing. Consequently, the objective of this paper is to propose the establishment of a fusion system integrating archaeological research on traditional culture with emerging virtual presentation technology. This paper draws inspiration from the replicability and easy dissemination of digital products to combine cultural archaeology and digital technology. The aim is to provide ideas for the diversity of dissemination of cultural heritage. The research object is Diplomatic Envoys, a Chinese mural painting of the Tang Dynasty that depicts friendly exchanges between countries. The research is divided into two research stages. A CLO3D software-based digital restoration test was conducted to reproduce the costumes of officials and foreign envoys depicted in the Tang Dynasty mural. The FAHP model was employed to verify the accuracy of the restoration results. The experiment demonstrated that the digitally reconstructed clothing exhibited a high degree of similarity to the unearthed mural figure clothing object. Furthermore, the restoration result passed the credibility verification, resulting in a ‘credible’ outcome. The application of digital virtual simulation clothing restoration methods offers two key advantages. Firstly, in comparison with traditional clothing restoration methods, digital restoration enables the rapid assessment of the resulting clothing effect, thereby reducing the likelihood of secondary damage to cultural relics due to manual errors. Secondly, the benefits of digital technology facilitate the convenient storage, replication, and dissemination of clothing data information. Data can not only be extended to online exhibition halls but also to game animation, clothing production, and other fields for the purposes of creative redesign and information dissemination. Furthermore, these benefits can penetrate the education industry to disseminate information to the public through all-round display models and explanations.

The Future of Fashion: Innovations in Virtual Try-on Systems

Our initiative aims to transform the online shopping experience and the fashion business by improving virtual try-on technology. Utilizing cutting-edge technologies like Graphonomy, Generative Adversarial Networks (GANs), and the U2 Net architecture, we suggest a Virtual Try-On Network (VTON) that provides incredibly lifelike and customized virtual clothing, accessories, and cosmetics based on each user's distinct facial features and body type. The smooth overlay of virtual products over user photos, accurate body posture capture, and exact garment segmentation are all made possible by the integration of these technologies. Our approach exhibits better performance than current methods, providing improved fit accuracy, visual fidelity, and user happiness, as proven by thorough testing and review. In the constantly changing world of digital retail, our project not only solves the shortcomings of conventional try-on techniques but also creates new opportunities for tailored shopping experiences and increased sales.

Investigating parameters affecting the real and virtual drapability of silk fabrics for traditional Hanbok

This paper presents research into the parameters affecting the real and virtual drapability of silk fabrics for traditional Hanbok. The KES-FB (Kawabata evaluation system of fabric) and the CLO (3D fashion design software) fabric kit system were used to evaluate the physical properties. The relationships between physical properties and the drape coefficient of silk fabrics were statistically analyzed. It was determined whether the objectified real fabric data could be used and applied as a database when implementing virtual clothing using a 3D virtual clothing program. The KES-FB properties and CLO fabric kit results indicated that the bending property and weight were significantly correlated with the drape coefficient. The bending rigidity and weight per unit area were influential parameters of the drape coefficient. The regression analysis results of both the KES-FB and the CLO fabric kit revealed that bending rigidity and thickness were statistically significantly correlated with the drape coefficient. The bending property was the most determining parameter for the drape coefficient of silk fabrics. A statistically significant difference between the real and virtual drape coefficients of stiffer silk fabrics was found. In the CLO 7.1 program, the accuracy of drape implementation of virtual fabrics was found to be useful when the bending stiffness of the actual fabric was less than 0.089 gf·cm2/cm and the elasticity was more than 1.03%. The results revealed that more research on the program modeling method considering the mechanical and physical properties of the real fabric and its structure is needed.

Enhancing Body Measurement Accuracy and Immersive Experience with Virtual/Augmented Reality in E – Commerce Platform

n the realm of e-commerce, achieving accurate body measurements for clothing is a persistent challenge. This project utilizes Virtual and Augmented Reality (VR/AR) technologies to revolutionize online shopping. It introduces a feature where users can enhance cloth fitting based on their measurements, reducing sizing issues and improving customer satisfaction. Users can input measurements like bust, waist, and hips to customize their fit, leading to a more seamless shopping experience and reducing returns. The project also includes a VR-based prototype for a virtual clothing store, enhancing engagement and aesthetics while redefining online apparel retailing standards. IndexTerms - Online Shopping,E-Commerce,ill-fiting,Virtual Reality,HTML,CSS,JavaScript

음양을 모티브로 이용한 태권도 격파용 도복 개발

Background/Objectives: Taekwondo, which originated in Korea, is a traditional martial art and sport that uses hands and feet to attack and defend. Uniforms specialized for Poomsae, Kyorugi, and Kyukpa can facilitate the use of techniques for each sport and reduce the risk of injury; however, except for the Kyorugi uniform, they are not further subdivided. This study develops the Kyukpa uniforms as they provide ease of movement and protection from injury, thereby leading to the globalization and popularization of Taekwondo. Methods: To develop 30 designs of Kyukpa uniforms and present virtual clothing using 3D CLO for four of these selected by fashion and Taekwondo experts, in-depth interviews were conducted based on theoretical research. After analysis, the final two sets were selected and produced. After producing the final two sets, this research proceeded by checking the ease of movement through a movement test with a Taekwondo player. Results: The final two sets of Kyukpa uniforms were selected and designed. It was a good compromise between a strong contrast and trendiness expressed through differentiated design and color while still keeping tradition in mind the terms of external aspects. The fitting evaluation and movement evaluation ensured that the uniforms were comfortable for movement and techniques. Conclusion/Implications: This study proposes a design approach that combines athleticism and reimagining the uniforms for each Taekwondo event. By specializing in Kyukpa uniforms with functionality, modern sophistication, and the symbolic elements of Taekwondo, we can significantly contribute to the global promotion and widespread adoption of this form of martial art.

A clothing pattern generating framework based on scanned human body model

PurposeAccurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.Design/methodology/approachPhysics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.FindingsThe results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.Originality/valueThe main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.

Stretchable spring‐sheathed yarn sensor for 3D dynamic body reconstruction assisted by transfer learning

AbstractA wearable sensing system that can reconstruct dynamic 3D human body models for virtual cloth fitting is highly important in the era of information and metaverse. However, few research has been conducted regarding conformal sensors for accurately measuring the human body circumferences for dynamic 3D human body reshaping. Here, we develop a stretchable spring‐sheathed yarn sensor (SSYS) as a smart ruler, for precisely measuring the circumference of human bodies and long‐term tracking the movement for the dynamic 3D body reconstruction. The SSYS has a robust property, high resilience, high stability (>18 000), and ultrafast response (12 ms) to external deformation. It is also washable, wearable, tailorable, and durable for long‐time wearing. Moreover, geometric, and mechanical behaviors of the SSYS are systematically investigated both theoretically and experimentally. In addition, a transfer learning algorithm that bridges the discrepancy of real and virtual sensing performance is developed, enabling a small body circumference measurement error of 1.79%, noticeably lower than that of traditional learning algorithm. Furtherly, 3D human bodies that are numerically consistent with the actual bodies are reconstructed. The 3D dynamic human body reconstruction based on the wearing sensing system and transfer learning algorithm enables excellent virtual fitting and shirt customization in a smart and highly efficient manner. This wearable sensing technology shows great potential in human‐computer interaction, intelligent fitting, specialized protection, sports activities, and human physiological health tracking.image

Implementasi Media Promosi Katalog Baju yang Lebih Interaktif Menggunakan Aplikasi Augmented Reality

The current technological advancement are progressing rapidly in line with the changing times. With the current pace of development, many people, especially teenagers, are keen on following fashion trends. This has led to increased competition in the fashion catalog industry. Many industries require information technology innovation, including the products offered to attract customers' attention. Typically, catalog industries advertise their products using posters, photos, or videos. However, these methods are less interactive and engaging as promotional media ideas in the current digital era. One technology that can address this issue is Augmented Reality (AR), which combines virtual objects with the real-world environment captured by the camera, making virtual objects appear integrated into the real world. By using Mobile Augmented Reality (AR) applications and with the help of our smartphones, we can view virtual clothing catalog objects on our smartphones, making them appear as if they were real. Moreover, users can virtually try on clothing over their own images, providing them with a better understanding of how the clothing will look when worn. This can create a more interactive and engaging shopping experience

Video Classification of Cloth Simulations: Deep Learning and Position-Based Dynamics for Stiffness Prediction.

In virtual reality, augmented reality, or animation, the goal is to represent the movement of deformable objects in the real world as similar as possible in the virtual world. Therefore, this paper proposed a method to automatically extract cloth stiffness values from video scenes, and then they are applied as material properties for virtual cloth simulation. We propose the use of deep learning (DL) models to tackle this issue. The Transformer model, in combination with pre-trained architectures like DenseNet121, ResNet50, VGG16, and VGG19, stands as a leading choice for video classification tasks. Position-Based Dynamics (PBD) is a computational framework widely used in computer graphics and physics-based simulations for deformable entities, notably cloth. It provides an inherently stable and efficient way to replicate complex dynamic behaviors, such as folding, stretching, and collision interactions. Our proposed model characterizes virtual cloth based on softness-to-stiffness labels and accurately categorizes videos using this labeling. The cloth movement dataset utilized in this research is derived from a meticulously designed stiffness-oriented cloth simulation. Our experimental assessment encompasses an extensive dataset of 3840 videos, contributing to a multi-label video classification dataset. Our results demonstrate that our proposed model achieves an impressive average accuracy of 99.50%. These accuracies significantly outperform alternative models such as RNN, GRU, LSTM, and Transformer.

Individually Integrated Virtual/Augmented Reality Environment for Interactive Perception of Cultural Heritage

The need to preserve and care for cultural heritage makes information technology a tool for finding, documenting, describing, and visualizing important historical and archaeological sites. This article offers an example of a demo platform providing users with a unique immersive experience in a virtual clothing museum environment. The proposed concept combines such types of media resources as audio, video, text, and 3D models of the virtual environment. The augmented reality elements perform the function of additional informing the users about certain facts about the exhibits. The methodology of platform development and the application's architecture are described. The creation of the platform is intended to achieve the objectives set by VR/AR technologies, namely, to provide a wide range of opportunities for interaction of the user with the objects of cultural heritage. The peculiarity of the application is the possibility to choose between exploring the objects of cultural heritage on one's own or following a programmed path with the help of an audio guide. The proposed solution can be used for stationary expositions of art objects, historical or archaeological relics, and objects of national economy and creativity. Testing of the demo version showed a rather high degree of user satisfaction (89% of respondents reported a positive experience). Users noted the atmospheric and immersive experience of virtual reality. The developed platform can perform educational and popularization functions.

Appearance flow estimation for online virtual clothing warping via optimal feature linear assignment

Clothing warping to spatially align source garments with the corresponding body parts is crucial in clothing media tasks such as virtual try-on and pose-guided person generation. Recent pioneering work has utilized flow fields with additional dimensions of freedom to simulate clothing warping flexibly. However, current methods for estimating appearance flow typically rely on calculating just the local cost volume which contains multiple noisy matching points, potentially leading to a mismatch between clothing and body parts. To address this issue, we propose a novel appearance flow estimation network(Warping-Flow) for clothing warping based on optimal features linear assignment. Specially, two remarkable contributions are made to improve feature matching precision. First, a local context feature aggregation module is proposed to enhance the semantic feature distinction of the source cloth and target pose. Second, Warping-Flow estimates a hard attention mask through the cost volume to filter irrelevant features, followed by the optimal linear assignment algorithm to normalize the cost volume to a discrete permutation matrix that explicitly models the most contributing bipartite matches. Experiments conducted on the VITON and VITON-HD datasets demonstrate that Warping-Flow outperforms existing state-of-the-art algorithms, particularly in cases involving complex clothing deformation. Furthermore, Warping-Flow can serve as a plug-in to improve existing garment media technologies.