• Proceedings of the Korea Fashion and Costume Design Association Conference
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• 2004.06a
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• pp.86-88
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• 2004

스포츠웨어는 현대사회의 건강과 여가에 대한 관심으로 단순한 운동복의 수준을 넘어 우리 일상생활의 한 부분으로 점차 정착되고 발전되었다. 특히 현대 패션은 다기능성이 부각된 의류의 수요가 증가되고, 스포츠웨어와 캐주얼웨어의 혼합, 스포츠웨어의 디테일이나 이미지를 도입한 일상복의 확대 등으로 스포츠패션이 두드러지게 나타나고 있다(한은주, 2002). 스포츠웨어의 개념은 미국에서 출발하여 발전되어왔다.(중략)

• Proceedings of the Korea Fashion and Costume Design Association Conference
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• 2004.06a
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• pp.11-12
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• 2004

흔히 사람들은 난 '옷을 몰라' 하면서도, 어떤 형태든 옷을 입는다. 그리고 그 옷을 입은 '최종형태'는 곧 그 사람의 이미지를 형성한다. 사실은 '어떤 옷을 입느냐' 로부터 자유로운 사람은 한 사람도 없다. 옷은 한 사람의 전체를 보여줄 뿐만 아니라, 오랜 세월 축적되면, 각 계급 계층, 지역, 국가의 특징이 고스란히 담기게 되고, 나아가 한 시대의 역사적인 모든 요소들을 반영하고 그 시대정신과 철학까지를 반영한다.(중략)

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.1
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• pp.65-81
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• 2023

The purpose of this study is to interpret the semantic actions of body image symbolized in body expression images shown by micro-influencers body profiles to understand the body profile phenomenon of the MZ generation. As a result of collecting body profile data from micro-influencers, the body profile image types of female influencers on SNS were classified into four types, Athletic, Slim body, Natural, and, Glamorous. Images representing each type were analyzed using the Roland Barthes' Myth model analysis frame. As a result of the semantic analysis, influencers were found to be very active and bold, emphasizing certain body parts according to the type of body image they pursue. Fashion is strategically used to emphasize these aspects. It was found that the ideology of a 'subjective modern woman' was commonly expressed through emphasis on visual signs. This study is meaningful in that it can indirectly lead to the understanding the fashion culture expressed by the MZ generation and provide consumer information and essential data that can be used for communication strategies in the fashion market.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.25-34
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• 2019

VTON (Virtual try-on) is a key technology that can activate the online commerce of fashion items. However, the early 3D graphics-based methods require the 3D information of the clothing or the human body, which is difficult to secure realistically. In order to overcome this problem, Image-based deep-learning algorithms such as VITON (Virtual image try-on) and CP-VTON (Characteristic preserving-virtual try-on) has been published, but only a sampled results on performance is presented. In order to examine the strength and weakness for their commercialization, the performance analysis is needed according to the complexity of the clothes, the object posture and body shape, and the degree of occlusion of the clothes. In this paper, IoU and SSIM were evaluated for the performance of transformation and synthesis stages, together with non-DL SCM based method. As a result, CP-VTON shows the best performance, but its performance varies significantly according to posture and complexity of clothes. The reasons for this were attributed to the limitations of secondary geometric deformation and the limitations of the synthesis technology through GAN.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.5
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• pp.17-25
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• 2019

In this paper, we introduce the technology to convert a single human image into a fashion show animation video clip. The technology can help the customers confirm the dynamic fitting result when combined with the virtual try on technique as well as the interesting experience to a normal person of being a fashion model. We developed an extended technique of full human 2D to 3D inverse modeling based on SMPLify human body inverse modeling technique, and a rigged model animation method. The 3D shape deformation of the full human from the body model was performed by 2 part deformation in the image domain and reconstruction using the estimated depth information. The quality of resultant animation videos are made to be publically available for evaluation. We consider it is a promising approach for commercial application when supplemented with the post - processing technology such as image segmentation technique, mapping technique and restoration technique of obscured area.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.11-18
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• 2020

Recently, a series of studies on virtual try-on (VTON) using images have been published. A comparison study analyzed representative methods, SCMM-based non-deep learning method, deep learning based VITON and CP-VITON, using costumes and user images according to the posture and body type of the person, the degree of occlusion of the clothes, and the characteristics of the clothes. In this paper, we tackle the problems observed in the best performing CP-VTON. The issues tackled are the problem of segmentation of the subject, pixel generation of un-intended area, missing warped cloth mask and the cost function used in the learning, and limited the algorithm to improve it. The results show some improvement in SSIM, and significantly in subjective evaluation.

• Proceedings of the Costume Culture Conference
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• 2006.04a
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• pp.46-47
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• 2006

• Proceedings of the Korea Society of Costume Conference
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• 2002.05a
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• pp.37-37
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• 2002

• Proceedings of the SOHE Conference
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• 2001.10a
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• pp.25-40
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• 2001

• Proceedings of KHEA Conference
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• 2003.10a
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• pp.90-90
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• 2003