• 대한인간공학회지
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• 제12권1호
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• pp.57-73
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• 1993

In this paper, methods of human figure representation in computer graphics are described. Many applications of the human figure representation are found in areas including industry, advertisement, and cartoon production and further research for the methods that show the human figure more realistically is ex- pected. Two analytic methods for human model, kinematics and dynamics, are ex- plained and the characteristics of the man-machine interface systems that include human figure representation are presented. Various techniques of the human figure representation based on kinematics or(and) dynamics are discussed and representation methods of human body segments such as hand, face, spine are introduced in this paper.

• 대한원격탐사학회지
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• 제21권5호
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• pp.393-404
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• 2005

As multi-source spatial data fusion mainly deal with various types of spatial data which are specific representations of real world with unequal reliability and incomplete knowledge, proper data representation and uncertainty analysis become more important. In relation to this problem, this paper presents and applies an advanced data representation methodology for different types of spatial data such as categorical and continuous data. To account for the uncertainties of both categorical data and continuous data, fuzzy boundary representation and smoothed kernel density estimation within a fuzzy logic framework are adopted, respectively. To investigate the effects of those data representation on final fusion results, a case study for landslide hazard mapping was carried out on multi-source spatial data sets from Jangheung, Korea. The case study results obtained from the proposed schemes were compared with the results obtained by traditional crisp boundary representation and categorized continuous data representation methods. From the case study results, the proposed scheme showed improved prediction rates than traditional methods and different representation setting resulted in the variation of prediction rates.

• 한국게임학회 논문지
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• 제6권4호
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• pp.39-45
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• 2006

게임개발에서 설계내용은 디자인단계에서 뿐 아니라 구현단계와 테스트단계까지 자주 변경이 이루어진다. 게임의 설계내용은 게임규칙과 콘텐츠의 설계내용으로 이루어진다. 그 중에서 게임규칙의 설계 내용은, 모든 개발참여자들이 쉽고 정확하게 이해할 수 있어야 하고 자주 이루어지는 변경들이 효율적으로 관리되어야 하며 그리고 정확한 검증이 이루어져야 한다. 본 연구는 게임규칙의 설계내용에 대해, 게임디자인에서 적합하게 될 수 있는 표현방식을 찾기 위한 조사연구로서, 문서표현방식, UML 표현방식, 페트리네트 표현방식, 스크립트언어 표현방식에 대해 비교분석을 하였다. 비교분석은 게임규칙의 표현범위, 비주얼적 표현능력, 논리적 표현능력, 자동화된 검증 가능성, 그리고 효율적 형상관리 가능성에 대하여 이루어졌다. 비교분석결과 UML 표기방식이 가장 적합하였다. 그러나 UML 표기방식은 보다 편리한 자동화된 검증 방법의 연구개발이 필요한 것으로 판단되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3745-3761
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• 2020

Low-rank representation methods already achieve many applications in the image reconstruction. However, for high-gradient image patches with rich texture details and strong edge information, it is difficult to find sufficient similar patches. Existing low-rank representation methods usually destroy image critical details and fail to preserve edge structure. In order to promote the performance, a new representation-based image super-resolution reconstruction method is proposed, which combines gradient domain guided image filter with the structure-constrained low-rank representation so as to enhance image details as well as reveal the intrinsic structure of an input image. Firstly, we extract the gradient domain guided filter of each atom in high resolution dictionary in order to acquire high-frequency prior information. Secondly, this prior information is taken as a structure constraint and introduced into the low-rank representation framework to develop a new model so as to maintain the edges of reconstructed image. Thirdly, the approximate optimal solution of the model is solved through alternating direction method of multipliers. After that, experiments are performed and results show that the proposed algorithm has higher performances than conventional state-of-the-art algorithms in both quantitative and qualitative aspects.

• 한국초등과학교육학회지:초등과학교육
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• 제39권2호
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• pp.204-218
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• 2020

This study aims to investigate the representation patterns used by elementary teachers and their meaning-making process in electromagnetic experiments. In particular, we analyzed the representations depending on three levels of their abstractness: enactive representation (action based), iconic representation (image based) and symbolic representation (language based). For this, four experiment activities of two teachers were analyzed and the results are as follows. First, as an overall pattern of representation, an experiment subject is presented as the form of symbolic representation and the related concepts, experimental materials and methods are embodied through iconic representation. Then, through enactive representation, the actual experiments are implemented. The experimental results are primarily recorded through iconic representations and abstracted into symbolic representations to draw conclusions. The different levels of representations complement each other to expand their meanings, however, sometimes they also make inconsistent meanings among different levels. Based on these results, educational implications were discussed in terms of supporting and improving electromagnetic experiment activities.

• 정보과학회 논문지
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• 제45권3호
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• pp.211-223
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• 2018

본 논문에서는 실내 서비스 로봇들을 위한 로봇 중심의 방향 관계 표현과 추론 방법을 제안한다. 정성적 공간 관계 추론에 관한 많은 기존 연구들에서는 기준 물체를 중심으로 대상 물체의 상대적 방향 관계를 판별할 때, 두 물체의 위치 정보만을 이용해왔다. 이러한 방향 관계 추론 방법들은 로봇 스스로가 기준 물체가 되어 다른 대상 물체들과의 방향 관계를 판별할 때, 로봇이 바라보고 있는 방향을 제대로 고려하지 않음으로써, 대상 물체의 방향 관계를 잘못 판별하는 사례들이 발생할 수 있다. 본 논문에서는 실내 환경에서 로봇을 중심으로 물체들의 상대적인 방향 관계를 판별할 때, 로봇의 위치 정보뿐만 아니라 로봇이 향하고 있는 방향 정보도 이용하는 로봇 중심의 방향 관계 표현과 방향 관계 추론 방법들을 제시한다. 로봇 중심의 방향 관계 추론 방법들은 두 물체의 위치 정보만을 이용해왔던 기존의 콘 기반 추론, 행렬 기반 추론, 그리고 혼합 추론 방법을 확장하여 구현하였다. 터틀봇과 시뮬레이션 로봇을 이용한 다양한 실험들을 통해, 본 논문에서 제안하는 방향 관계 표현과 추론 방법들의 높은 성능과 적용 가능성을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권6호
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• pp.2709-2729
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• 2016

Representation based classification, kernel method and sparse representation have received much attention in the field of face recognition. In this paper, we proposed an improved kernel principal component analysis method based on sparse representation to improve the accuracy and robustness for face recognition. First, the distances between the test sample and all training samples in kernel space are estimated based on collaborative representation. Second, S training samples with the smallest distances are selected, and Kernel Principal Component Analysis (KPCA) is used to extract the features that are exploited for classification. The proposed method implements the sparse representation under ℓ₂ regularization and performs feature extraction twice to improve the robustness. Also, we investigate the relationship between the accuracy and the sparseness coefficient, the relationship between the accuracy and the dimensionality respectively. The comparative experiments are conducted on the ORL, the GT and the UMIST face database. The experimental results show that the proposed method is more effective and robust than several state-of-the-art methods including Sparse Representation based Classification (SRC), Collaborative Representation based Classification (CRC), KCRC and Two Phase Test samples Sparse Representation (TPTSR).

• 대한수학교육학회지:수학교육학연구
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• 제14권1호
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• pp.39-69
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• 2004

본 연구에서는 학생들이 일차함수의 활용단원을 학습할 때 여러 현상을 해석하고 다양한 수학적 표현을 사용하여 모델로 만들어 문제해결과정에 이를 적용할 수 있도록, 학생들의 표현에 대한 이전 경험과 현상을 해석하기 위한 표현 방법을 효과적으로 연결하는 학습-지도 방법을 분석하였다. 본 연구는 일차함수를 학습한 8학년 학생들을 대상으로 일차함수 단원을 예측과제, 번역과제, 해석과제, 척도과제로 세분화하여 각각에 대한 학생들의 오류를 분석한 다음, 일차함수의 활용 단원을 교과서 위주의 강의식 표현변환 학습, 모델링 관점에서의 표현변환 학습과 과제기반 표현변환 학습을 실시하였다. 연구 결과, 강의식 학습 방법보다는 모델링 관점과 과제기반 학습이 표현변환의 유연한 연결성 및 일차함수에 대한 각 과제별 오류교정과 질적 함수에 대한 해석 능력에서 효과적이었다. 모델링 관점과 과제기반 학습의 경우는 모두 표현변환의 유연한 연결을 교수하는데 효과적이었으나, 질적 함수의 해석 능력에서는 모델링 관점의 학습이 보다 효과적이었다.

• 한국수학교육학회지시리즈C:초등수학교육
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• 제8권1호
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• pp.23-32
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• 2004

It is not too much to say that problem solving is still the focus of school mathematics though the trend of mathematics education for ten year from the one of 1980 is problem solving and the one of mathematics education for ten year from the one of 1990 is standards and constructivism. There are so many crucial clues or methods in good problem solving but I think that one of them is a representation. So, the purpose of this study is to investigate what is the meaning of representation in general and why representation is so important in elementary mathematics learning, Moreover, I have analyzed the gifted children's thinking of representation which is appeared in the previous internet home task of 40 gifted children who are selected through the examination of 1st, 2nd with paper and pencil and 3rd with practical skill and interview and finally I have presented some examples of children's representation how they use representation to model, investigate and understand special concept more easily in elementary school mathematics class.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.283-286
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• 2001

Based on a fuzzy system representation of gray scale images, we derive an edge detection algorithm whose convolution kernel is different from the known kernels such as those of Roberts', Prewitt's or Sobel's gradient. Our fuzzy system representation is an exact representation of the bicubic spline function which represents the gray scale image approximately. Hence the fuzzy system is a continuous function and it provides a natural way to define the gradient and the Laplacian operator. We show that the gradient at grid points can be evaluated by taking the convolution of the image with a 3 3 kernel. We also show that our gradient coupled with the approximate value of the continuous function generates an edge detection method which creates edge images clearer than those by other methods. A few examples of applying our methods are included.