• Proceedings of the Korea Society of Costume Conference
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• 2005.10a
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• pp.216-217
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• 2005

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.216-217
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• 2007

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.171-187
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• 2023

When a person's face is recognized through a recording device such as a low-pixel surveillance camera, it is difficult to capture the face due to low image quality. In situations where it is difficult to recognize a person's face, problems such as not being able to identify a criminal suspect or a missing person may occur. Existing studies on face recognition used refined datasets, so the performance could not be measured in various environments. Therefore, to solve the problem of poor face recognition performance in low-quality images, this paper proposes a method to generate high-quality images by performing image quality improvement on low-quality facial images considering various environments, and then improve the performance of facial feature point detection. To confirm the practical applicability of the proposed architecture, an experiment was conducted by selecting a data set in which people appear relatively small in the entire image. In addition, by choosing a facial image dataset considering the mask-wearing situation, the possibility of expanding to real problems was explored. As a result of measuring the performance of the feature point detection model by improving the image quality of the face image, it was confirmed that the face detection after improvement was enhanced by an average of 3.47 times in the case of images without a mask and 9.92 times in the case of wearing a mask. It was confirmed that the RMSE for facial feature points decreased by an average of 8.49 times when wearing a mask and by an average of 2.02 times when not wearing a mask. Therefore, it was possible to verify the applicability of the proposed method by increasing the recognition rate for facial images captured in low quality through image quality improvement.

• Fashion & Textile Research Journal
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• v.17 no.5
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• pp.731-740
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• 2015

Mobile (smartphone) search engine marketing is increasingly important. Accordingly, the development of visual apparel search technology to obtain easier and faster access to visual information in the apparel field is urgently needed. This study helps establish a proper classifying system for an apparel search after an analysis of search techniques for apparel search applications and existing domestic and overseas apparel sites. An annotation technique is developed in accordance with visual attributes and apparel categories based on collected data obtained by web crawling and apparel images collecting. The categorical composition of apparel is divided into wearing, image and style. The web evaluation site traces the correlations of the apparel category and apparel factors as dependent upon visual attributes. An appraisal team of 10 individuals evaluated 2860 pieces of merchandise images. Data analysis consisted of correlations between apparel, sleeve length and apparel category (based on an average analysis), and correlation between fastener and apparel category (based on an average analysis). The study results can be considered as an epoch-making mobile apparel search system that can contribute to enhancing consumer convenience since it enables an effective search of type, price, distributor, and apparel image by a mobile photographing of the wearing state.

• 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.

• Journal of the Korean Home Economics Association
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• v.40 no.2
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• pp.29-37
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• 2002

The purpose of this study was to examine the effects of bodyshape and clothing color on boy's impression. The subjects were composed of 480 elementary students, 11-12 years old. The stimuli were consisted of 12 color photographs by using CAD system that was different in the bodyshape, the clothing color and the level of contained color each other. The subjects reported the stimuli's pression on the questionnaires. The image of the stimuli were emerged 5 differented dimensions ; attractiveness, evaluation, potency, bodyshape, visibility. The boy's impressions of normal bodyshape were more attractive, positive evaluation and thin than obese bodyshape. The boy's impressions who was dressed in pink color shirt were thin than blue color. The boy's impressions were positive evaluation when he was dressed in shirt with pink or blue color in collar and cuffs and the whole. The boy's impression of normal bodyshape wearing blue color shirt was the most attractive but the boy's impression of obese bodyshape wearing pink color shirt was not charm. The boy's evaluation who was normal bodyshape wearing pink color shirt was the most positive and the most thin.

• The Research Journal of the Costume Culture
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• v.14 no.1
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• pp.93-107
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• 2006

This study was designed from the concept that there is a need to establish the uniform for new emerging jobs in modern society. The purpose of the study was to examine dental hygienists'wearing condition, satisfaction, and design evaluation as to provide information for the development of dental hygienists' uniform. Three hundred fifteen dental hygienists completed questionnaires, and data were analyzed by descriptive statistics, factor analysis, multiple regression, ANOVA, and Duncan's test. The findings from the study were following. First, majority of dental hygienists currently wear shirts and pants two-piece uniform in white with no print. Second, dental hygienists' overall satisfaction level for their uniform was medium, and symbolic satisfaction as well as functional satisfaction did not reach the medium level while aesthetic satisfaction was above medium. The satisfaction levels were significant different between groups according to the education, clinic size, and work experience. Third, aesthetic satisfaction levels influenced on the job image as professional. Finally, designs consisting of two-piece style with shirts and pants and having Peter pan collar were recorded high evaluation. The findings can be implemented into dental hygienists' uniform design.

• Fashion & Textile Research Journal
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• v.6 no.5
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• pp.549-557
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• 2004

The purpose of this study is to investigate design properties affecting in evaluated image by adult women's town wear in un-limited circumstance. The stimulus, adult women's town wear, were collected from shopping mall, department stores and churches and evaluated by 20's 150 people. Through the estimations, the 76 pictures of 'good image' and 65 pictures of 'bad image', were selected and analyzed by classification categories. The results were as follows : 1) 'Good Image' is classified 6 groups which are like active casual, feminine casual, adult casual, modern, sporty casual, and elegance. 2) "Bad Image' is classified 5 groups which are like easy casual, active casual, soft casual, modern casual, and feminine casual. 3) Central code of adult women's town wear from 'Good Image' are simple, bright, and harmony and 'Bad Image' are complicate, heavy, and inharmony. The coordination, how to wear, is very important to evaluate image of women's town wear with other properties. Also, body shape appeared by important variable in evaluation.

• International Journal of Costume and Fashion
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• v.10 no.2
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• pp.51-59
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• 2010

This study regarded fashion selection criteria as clothing consumption value and desired fashion images, and examined selection differences according to regional subculture groups. Clothing consumption value is a direct value that people seek with clothing products and a perceived value which is divided into emotional, social, price, quality values. Fashion image which is a feeling communicated to others by wearing a certain fashion style is the most superficial value. Multivariate Analysis of Variance (MANOVA) was performed to test the differences between regional subculture groups in clothing consumption values and desired fashion images. We found some differences in clothing consumption value specifically in emotional value and social value. The group differences were remarkably significant in fashion image comparison. 'Kang-nam' group pursued 'lively', 'sophisticated', 'charming', feminine', 'gorgeous' image more than 'Kang-buk' group. While 'Kang-buk' group produced lower scores in ideal fashion images, the group had significant higher seeking in 'sportive' image compared to 'Kangnam' group.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.186-203
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• 2020

Image-based Virtual Try-On Systems are among the most potential solution for virtual fitting which tries on a target clothes into a model person image and thus have attracted considerable research efforts. In many cases, current solutions for those fails in achieving naturally looking virtual fitted image where a target clothes is transferred into the body area of a model person of any shape and pose while keeping clothes context like texture, text, logo without distortion and artifacts. In this paper, we propose a new improved image-based virtual try-on network system based on keypoints, which we name as KP-VTON. The proposed KP-VTON first detects keypoints in the target clothes and reliably predicts keypoints in the clothes of a model person image by utilizing a dense human pose estimation. Then, through TPS transformation calculated by utilizing the keypoints as control points, the warped target clothes image, which is matched into the body area for wearing the target clothes, is obtained. Finally, a new try-on module adopting Attention U-Net is applied to handle more detailed synthesis of virtual fitted image. Extensive experiments on a well-known dataset show that the proposed KP-VTON performs better the state-of-the-art virtual try-on systems.