• Archives of design research
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• no.18
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• pp.75-84
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• 1996

모든 예술적 표현 활동은 서로 깊은 연관을 지니고 있으며, 복식 디자인 역시 예술적 표현 활동의 한 분야로서, 현대에 이르러 복식은 단순히 입는다는 개념을 탈피한 하나의 조형 예술로 인식되어지고 있다. 예술적 표현 활동은 조형 제작 활동의 주체인 인간이 예술적 표현의 의지를 사물로 객체화하는 과정에 있어서, 그 재료와 재료의 가공 기법을 통해 표현되는 활동이라고 말할 수 있다. 근자에 이르러 종이는 예술표현 활동에 있어서 진정한 표현 매재로 간주되고 있으며, 특히 종이를 예술적 표현을 위한 피동적 표면이라는 재료로서의 고정된 관념에서 탈피하여 입체적 조형이 시도되고, 이러한 종이의 입체로의 성형 가능성에 대한 발견은 조형 매체로서의 종이에 대한 새로운 시각을 제시하고 있다. 이에 본 연구는 종이 조형에 의해 표현되는 조형성을 복식에 적용시키기 위한 것으로서, 종이를 통한 조형성 표현의 여러 방법 중 특히 접기의 방법을 응용하여, 접기 기법의 조형요소로서의 특성과 인체와 결합하여 복식으로 이루어졌을 때 새로운 조형물로 인식되어질 수 있는 복식의 형태를 시도하였다. 작품은 접기 기법에 의해 형성되는 조형성을 복식을 응용하여, 복식에 대한 기하학적 조형성과 함께 새로운 실루엣과 이미지를 창출하며, 복식의 새로운 표현 영역의 확대를 위한 실물 작품으로 제작하였다.

• Cartoon and Animation Studies
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• s.49
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• pp.651-676
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• 2017

Shadow images are a representative medium and means of expression for the imagination that exists between consciousness and unconsciousness for thousands of years. Wherever light exists, people create play with their own shadows without special skills, and have made a fantasy at once. Shadow images have long been used as subjects and materials of literacy, art, philosophy, and popular culture. Especially in the field of art, people have been experimenting with visual stimulation through the uniqueness of simple silhouettes images. In the field of animation, it became to be recognized as a form of non - mainstream areas that are difficult to make. However, shadow images have been used more actively in the field of digital arts and media art. In this Environment with technologies, Various formative imaginations are being expressed more with shadow images in a new dimension. This study is to introduce and analyze these trends, the aesthetic transformations and extended methods focusing on digital silhouette animation and recent media art works using shadow images. Screen-based silhouette animation combines digital technology and new approaches that have escaped conventional methods have removed most of the elements that have been considered limitations, and these factors have become a matter of choice for the directors. Especially, in the display environment using various light sources, projection, and camera technology, shadow images were expressed with multiple-layered virtual spaces, and it becomes possible to imagine a new extended imagination. Through the computer vision, it became possible to find new gaze and spatial images and use it more flexibly. These changes have given new possibility to the use shadow images in a different way.

• Journal of the Korea Computer Graphics Society
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• v.12 no.1
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• pp.17-20
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• 2006

본 논문에서는 실사 렌더링에서 디테일한 조명 효과를 위해 쓰이는 범프 매핑 기술을 이용하여 기하적으로 복잡한 지오메트리를 표현하되, 이미지 스페이스상의 실루엣 검출 기법과 카툰 쉐이딩을 적용하여 만화적인 스타일을 연출하였다. 이 연구를 통해 기존의 카툰 렌더링된 3D 씬에 범프매핑으로 표현된 오브젝트가 자연스럽게 어울릴 수 있고, 빌보드 이미지에도 카툰 렌더링을 적용하여 빛에 대한 변화 효과를 보여줄 수 있다.

• The Journal of Natural Sciences
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• v.17 no.1
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• pp.79-87
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• 2006

Now thus season trend, we can see the multi and digital trend. Specially it was very sensational in fur trend. Many designer showed very shocking and mixed design, silhouette is bulky and fusion short. The background are rise up of kidult, naturalism, techno casual sense, new avangarde. Now, fur is not the classic item anymore. It is necessary to change funny and trendy casual item.

• Fashion & Textile Research Journal
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• v.14 no.2
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• pp.184-192
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• 2012

This study analyzed silhouette expressions in the fashion illustrations by theory based on results of studying the characteristics of the forms and meanings of the silhouette expressions in art historically. For the actual considering this study collected and categorized fashion illustrations from 1990 to the present limitedly, and clarified the meaning of the silhouette expressions. Those expressions in fashion illustrations were categorized to the 5 items; black & white silhouette, color silhoutte, pattern silhouette, paper silhouette, line silhouette. Silhouette expressions of the fashion illustrations were categorized to 3 items: metaphorical fantasy, essential minimization, anonymous representation.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.10
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• pp.777-788
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• 2006

This paper describes a displacement mapping technique which represents protruded shapes on the surface of an object. Previous approaches for image-based displacement mapping can represent only shapes depressed from the polygon surface. The proposed technique can represent shapes protruded from the underlying surface in real-time. Two auxiliary surfaces which are perpendicular to the underlying surface are added along the boundary of the polygon surface, in order to represent the pixels which overflow over the boundary of the polygon surface. The proposed approach can represent accurate silhouette of protruded shape. It can represent not only smooth displacement of protruded shape, but also abrupt displacement such as perpendicular protrusion by means of adding the supplementary texture information to the steep surface of protruded shape. By per-pixel instructions on the programmable GPU this approach can be executed in real-time. It provides an effective solution for the representation of protruded shape such as high-rise buildings on the ground.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.53-64
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• 2009

This paper presents a performance evaluation of shape descriptors for gait analysis in case of silhouette sequence images. We used moment descriptors(MD), Fourier descriptors(FD) and Zernike descriptors(ZD) as a shape descriptor. To evaluate their performance, we firstly defined the performance index, that is, AI(asymmetry index) and PI(periodic index) based on the periodic property of the gait images. This is why they are represented by periodic parameters due to periodic gait images. This index means that how the shape is represented periodically. According to these indexes, we evaluated the data sets with periodic images, downloaded from internet. The results showed that Zernike descriptors had better performance of AI = 1.09 and PI = 2.21 than others. And in case of FD and ZD, it's efficient to implement the gait analysis with 5~10 parameters.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.960-966
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• 2009

A manifold is used to represent a relationship between high-dimensional data samples in low-dimensional space. In human pose estimation, it is created in low-dimensional space for processing image and 3D body configuration data. Manifold learning is to build a manifold. But it is vulnerable to silhouette variations. Such silhouette variations are occurred due to view-change, person-change, distance-change, and noises. Representing silhouette variations in a single manifold is impossible. In this paper, we focus a silhouette variation problem occurred by view-change. In previous view invariant pose estimation methods based on manifold learning, there were two ways. One is modeling manifolds for all view points. The other is to extract view factors from mapping functions. But these methods do not support one by one mapping for silhouettes and corresponding body configurations because of unsupervised learning. Modeling manifold and extracting view factors are very complex. So we propose a method based on triple manifolds. These are view manifold, pose manifold, and body configuration manifold. In order to build manifolds, we employ biased manifold learning. After building manifolds, we learn mapping functions among spaces (2D image space, pose manifold space, view manifold space, body configuration manifold space, 3D body configuration space). In our experiments, we could estimate various body poses from 24 view points.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.23-30
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• 2005

As a human identification technique, gait recognition has recently gained significant attention. Silhouette-based gait recognition is one of the most popular methods. This paper aims to investigate features that determine the style of walking in silhouette-based gait recognition. Gait can be represented using two cues: static(shape) cue and dynamic(motion) cue. Most recently, research results have been reported in the literature that the characteristics of gait are mainly determined by static cue but not affected by dynamic cue. Unlike this, experimental results in this paper verifies that dynamic cue is as important as and in many cases more important than static cue. For experiments, we use two well-blown gait databases: UBC DB and Southampton Small DB. The images of UBC DB correspond to the 'ordinary' style of walking. The images of Southampton Small DB correspond to the 'disguised' (not ordinary by wearing special clothes or bags) style of walking. As results of experiments, the recognition rate was 100% by static cue and $95.2\%$ by dynamic cue for the images of UBC DB. For the images of Southampton Small DB, the recognition rate was $50.0\%$ by static cue and $55.8\%$ by dynamic cue. The risk against correct recognition was 0.91 by static cue and 0.97 by dynamic cue for the images of UBC DB. For the images of Southampton Small DB, the risk was 0.98 by static cue and 0.98 by dynamic cue. Consequently, the characteristics of ordinary gait are mainly determined by static cue but that of disguised gait by dynamic cue.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.95-105
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• 2006

This paper proposes a novel approach to represent the image by using shape descriptor having an information of area. The proposed descriptor is a set of vectors, consists of radius, area and direction parameters in the concentrated center point. Due to the area parameter, we know our descriptor can obtain the information of area. Also, we give an extended shape descriptor to get more detailed representation. To do this, we move the center point of our vision to that point for region of interest. By doing so about all of region of interest, we can get our descriptor for detailed information of the image. From more detailed descriptor, it's natural that it's more efficient fur representation, retrievals and so on. We make it the normalized pattern and expand to improve its quality. The proposed method is invariant to scale, position and rotation. The results show that it can be used efficiently for image representation as we can see in retrievals of silhouette images.