• Fashion & Textile Research Journal
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• v.23 no.2
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• pp.247-260
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• 2021

While it is an important element of clothing construction, research has so far been very limited on the similarities between virtual and real clothing in terms of the type of neckline. The purpose of this study is to verify the similarity, accuracy of virtualization, and actuality of neckline, which all play an important role in individual impressions and image formation, and require considerable modification when fitting real samples. A total of 5 neckline models were selected through the analysis of dress composition textbooks. The selected designs were then planned and manufactured in muslin. The specimen clothes were then tested on a female model in her 20s. 2 kinds of virtual bodies were created in order to compare the real and the virtual dressing. The first virtual body was made through an Artec 3D Eva scan of the model, and the other was made by entering the model's measurements in a CLO 3D program. A visual image of the front, side, and back image of both the real and virtual dressing were subsequently collected. The collected images were then evaluated by 20 professional fashion workers who checked the similarity between the real and the virtual versions. The current study found that the similarity between the actual and virtual wearing of the five neckline designs with reality appeared higher with the virtual wearing image using the 3D-scanned body. The results of this study could provide further information on the selection of appropriate avatars to clothing companies that check the fit of clothing by utilizing 3D virtualized programs.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.138-147
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• 2022

Recently, chatbots have been applied in various fields and have shown good results, and many attempts to use chatbots in shopping mall product recommendation services are being conducted on e-commerce platforms. In this paper, for a conversation system that recommends a fashion that a user wants based on conversation between the user and the system and fashion image information, a transformer model that is currently performing well in various AI fields such as natural language processing, voice recognition, and image recognition. We propose a multimodal-based improved transformer model that is improved to increase the accuracy of recommendation by using dialogue (text) and fashion (image) information together for data preprocessing and data representation. We also propose a method to improve accuracy through data improvement by analyzing the data. The proposed system has a recommendation accuracy score of 0.6563 WKT (Weighted Kendall's tau), which significantly improved the existing system's 0.3372 WKT by 0.3191 WKT or more.

• Journal of the Korean Home Economics Association
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• v.44 no.7 s.221
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• pp.153-162
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• 2006

This study was attempted to investigate the possibilities of fitness evaluation of virtual model using 3D clothes modeling software. For the purpose, two one-piece dresses were made with two kinds of patterns using Qualoth program, and then each dress was fitted to a real model and a virtual model, and the results were compared and discussed. The result of this study was as follows. First, the fitness evaluation of real model showed a significant difference only at a little difference in figures (1-2.5cm) of the pattern, while any significant difference in appearance was not found in case of a virtual model fitted a dress made out of a pattern with the same difference in figures. Second, items to evaluate a difference in patterns using 3D clothes modeling software were shoulder line, the distance between shoulder points, armhole line, ease of armscye depth, and overall appearance. Because all the items fall under design lines which make up outer lines of a cloth, it can be said that the Qualoth program is good for representing design, rather than exposing a small difference in patterns.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.85-96
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• 2015

Despite the growth of body-related industry has generated considerable interest in this topic among both academics and practitioners, there has been lack of studies that explore body esteem toward online fashion products leads to purchase intentions, which self-monitoring moderates the relationship between body esteem toward online fashion products and purchase intentions. To fill this gap, this study aim to propose a research model where body esteem influences on the purchase intentions, with self-monitoring as a moderator. In order to test hypotheses, response from 172 consumers were achieved, and the proposed model was estimated by using hierarchical moderated regression analysis. The empirical results showed that body esteem negatively related to purchase intentions toward online fashion products. Additionally, this study indicated that the moderating effects of self-monitoring exist between body esteem and purchase intentions toward online fashion products, thereby implying the importance of contingent role of self-monitoring in managing online channels.

• Journal of the Korean Society of Costume
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• v.54 no.4
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• pp.63-74
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• 2004

This study shows that clothes to be just the same as the real thing can be Produced through the third dimension computer graphics, and then presents that not only the area of fashion design can be expanded in the virtual reality field by doing the simulation of the fashion show, but also the information can be made the real time public ownership and the communication can be fulfilled smoothly. In this study, analyzing the third dimension computer graphic programs to be used much at present, Alias Wavefront Company's Maya software which was the most effective in the clothes simulation and the clothes CAD SGS OptiTex 8.7 which went well substitutive for it were used of them. The conclusions of this study that got through the work manufacture are as follows： The first, if the file manufacturing in the clothes CAD by using the computer was stored, the pattern used 3D simulation was available because it could be summoned in 3D software. The second, if the data of DXF form in Maya program was summoned, they could not be applied by Maya Cloth supported in Nurbs only because they were recognized as the DXF＿layer. So the curve along the outer lines of the pattern was drawn and Maya Cloth was applied to be possible to get the natural silhouette of clothes. The third, when the clothes were manufactured by 3D, if the draping character was applied according to the textile special quality, not only the control of textile's thickness, weight, quality feeling, and silhouette was available, but also the clothes were available to graft the special textile materials. The fourth, the natural motion of model was produced by capturing the actual model's walking action In order to produce the fashion show motion and also the dynamic fashion show was available by the angle of camera, the establishment of lighting, and etc. in the final rendering. The clothes manufactured by 3D are available to change the design by changing the materials, or by adding the details, or by utilizing the special materials on clothes. Therefore, the trial and error following at the clothes manufacture can be reduced. But the elevation of the rendering speed, the price down, the strengthening of personal security, and etc. are required.

• The Research Journal of the Costume Culture
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• v.29 no.4
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• pp.554-571
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• 2021

The purpose of this study is to investigate the mediating effect of trust when a media broadcaster (such as a disc jockey [DJ]) acting as an information source and the content they provide during live commerce streaming affect acceptance intention. Live commerce is increasing rapidly, offering a new fashion distribution channel by supplementing possible shortcomings of existing online shopping. Data was collected for the empirical study from female consumers in their 20s who actively accepted fashion technology. Statistical analysis of the data was conducted using IBM SPSS Macro Process 3.5. First, the reliability and validity of the variables for information source characteristics, content informativeness, trust, and acceptance intention were verified, and each variable was confirmed as a single factor. Bootstrap analysis was performed using Macro Process Model 4 to reveal the effects of information source characteristics and content informativeness on acceptance intention. As a result of analyzing the mediating effect for each path model with trust as a parameter, it was found that both the direct and indirect effects of the mediating path were significant. This result means that the characteristics of information sources and content informativeness are partially mediated by trust. Therefore, to promote consumer behavior in a live commerce shopping environment, it is necessary to enhance trust. This can be achieved by a media broadcaster with fashion expertise to increase the perception of the attractiveness of the information source and to improve the usefulness of the fashion information being delivered.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.3
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• pp.464-480
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• 2022

With the steady development of Artificial Intelligence (AI), online stores are adopting chatbot services as virtual shopping assistants. This study proposes the concept of para-social presence to explore the undiscovered role of fashion chatbots' emotional and relational characteristics on service acceptance. Based on the Technology Acceptance Model (TAM), this study investigates the effect of a chatbot's para-social presence on service acceptance intention through consumers' beliefs. The web-based experiment was conducted on adult consumers who experienced chatbot services in an online shopping situation. A total of 247 responses were analyzed using confirmatory factor analysis, structural equation modeling, and multi-group SEM by AMOS 21.0 and SPSS 23.0. The findings illustrate that the chatbot's intimacy positively influenced consumers' perceived enjoyment, while the chatbot's understanding had a significant effect on perceived usefulness and ease of use. The chatbot's involvement had a positive effect on all consumer beliefs. Moreover, perceived ease of use had a positive influence on usefulness. A greater level of perceived usefulness and enjoyment positively heightened consumers' service acceptance intention. This study also verifies the moderating role of a need for human interaction. Consumers with a high need for human interaction have a relatively low tendency to perceive chatbot services as useful.

• Human Ecology Research
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• v.61 no.3
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• pp.389-399
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• 2023

Sustainable fashion products have different characteristics from typical fashion products. Therefore, this study focuses on shoes while exploring the expansion and development of sustainable fashion consumption as well as consumers' perceptions of the sustainability approaches practiced by shoe companies. In-depth interviews were conducted with 24 consumers, who had purchased sustainable shoes, in order to understand their purchase decision-making process and consumption characteristics, using the seven stages of the EBM model. In the "need recognition" stage, the survey participants' social background and family influences were categorized as macro factors, while their personal background influences were categorized as micro factors. In the "evaluation of alternatives" stage, participants reconfirmed whether or not to make a purchase based on the product's properties, such as price, brand value, and offered services. In the "purchase" stage, participants' purchase channels were determined according to their preferences as well as the selection pattern they followed until the final purchase within the chosen channel. In the "consumption" stage, the start of product ownership coincides with the start of using the products after making a purchase. In the "post-purchase assessment" stage, higher positive experiences led to a higher repurchase intention of sustainable shoes, while negative experiences caused participants to defer consumption and made them experience a sense of guilt for failing to consume sustainably. During the "post-purchase behavior" stage, which focused on the categories that the customers prioritized, many participants spread information about sustainable fashion to specific individuals through active online WOM behavior.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.465-467
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• 2022

Mobile phones have become an essential item nowadays since it provides access to online platform and service fast and easy. Coming to these platforms such as Social Network Service (SNS) for shopping have been a go-to option for many people. However, searching for a specific fashion item in the picture is challenging, where users need to try multiple searches by combining appropriate search keywords. To tackle this problem, we propose a system that could provide immediate access to websites related to fashion items. In the framework, we also propose a deep learning model for an automatic analysis of image contexts using instance segmentation. We use transfer learning by utilizing Deep fashion 2 to maximize our model accuracy. After segmenting all the fashion item objects in the image, the related search information is retrieved when the object is clicked. Furthermore, we successfully deploy our system so that it could be assessable using any web browser. We prove that deep learning could be a promising tool not only for scientific purpose but also applicable to commercial shopping.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.31-40
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• 2024

In the realm of domestic online fashion platform industry the manual registration of product information by individual business owners leads to inconvenience and reliability issues, especially when dealing with simultaneous registrations of numerous product groups. Moreover, bias is significantly heightened due to the low quality of product images and an imbalance in data quantity. Therefore, this study proposes a ResNet50 model aimed at minimizing data bias through oversampling techniques and conducting multiple classifications for 13 fashion categories. Transfer learning is employed to optimize resource utilization and reduce prolonged learning times. The results indicate improved discrimination of up to 33.4% for data augmentation in classes with insufficient data compared to the basic convolution neural network (CNN) model. The reliability of all outcomes is underscored by precision and affirmed by the recall curve. This study is suggested to advance the development of the domestic online fashion platform industry to a higher echelon.