• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.903-906
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• 2001

본 논문에서는 조명의 변화에 의해 컬러 영상의 컬러 성분이 달라지더라도 영상 내 컬러간의 편차값을 나타내는 공분산 행렬(covariance matrix)의 고유벡터(eigenvector)와 영상 내 화소들의 컬러 성분과의 상관관계는 거의 변화하지 않는 특징을 이용한 조명 변화에 강인한 영상 검색 방법을 제안한다. 제안된 방법은 영상에서 컬러 성분들의 공분산 행렬과 공분산 행렬의 고유치(eigenvalue), 고유벡터를 계산한 후, 가장 큰 고유치에 관계된 고유벡터로 화소를 투영시키고, 투영된 벡터의 크기 성분으로 영상을 재구성한다. 재구성된 영상으로부터 7개의 불변 모멘트(moment)를 계산하고, 공분산의 가장 큰 고유치를 가중치로 부과하여 특징벡터를 추출한다. 7개의 불변 모멘트로부터 구한 특징벡터는 영상 내 물체의 이동, 영상의 회전, 크기 변화뿐만 아니라, 조명의 변화에 의해 컬러가 변화할 경우에도 유사한 영상을 잘 검색한다. 제안된 방법의 성능 확인을 위하여 5가지 조명에서 얻은 영상 데이터베이스를 이용하여 실험하였으며, 실험 결과 히스토그램 인터섹션에 비해 적은 특징량으로 검색이 가능하면서 조명 변화에도 대응할 수 있는 검색 결과를 얻을 수 있었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3C
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• pp.264-270
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• 2010

Non-planar screens such as cylinder and sphere shaped screens are widely used for high-resolution immersive visualization environments. An existing method employs quadric matrix that maps an image onto a curved screen. However if the shape of the screen changes or moves, the quadric matrix will not be valid. In this paper, we assume that the screen is a quadric shape and the screen movement or change are relatively small. Then we propose to use a piecewise planar approximations for the screen to compensate for the geometric distortion on a non-planar screen. We demonstrate the effectiveness and efficiency of the proposed method through experiments.

• Journal of Korea Multimedia Society
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• v.7 no.10
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• pp.1478-1484
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• 2004

This paper presents a method that controls facial expression in realtime of 3D avatar by having the user select a sequence of facial expressions in the space of facial expressions. The space of expression is created from about 2400 frames of facial expressions. To represent the state of each expression, we use the distance matrix that represents the distances between pairs of feature points on the face. The set of distance matrices is used as the space of expressions. Facial expression of 3D avatar is controled in real time as the user navigates the space. To help this process, we visualized the space of expressions in 2D space by using the Principal Component Analysis(PCA) projection. To see how effective this system is, we had users control facial expressions of 3D avatar by using the system. This paper evaluates the results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.1-7
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• 2007

In this paper, we analyze geometrical relations of 3D shape reconstruction from 2D images taken under anne projection. The purpose of this research is to contribute to more accurate 3-D reconstruction under noise distribution by analyzing geometrically the 2D to 3D relationship. In situation for no missing feature points (FPs) or no noise in 2D image plane, the accurate solution of 3D shape reconstruction is blown to be provided by Singular Yalue Decomposition (SVD) factorization. However, if several FPs not been observed because of object occlusion and image low resolution, and so on, there is no simple solution. Moreover, the 3D shape reconstructed from noise-distributed FPs is peturbed because of the influence of the noise. This paper focuses on analysis of geometrical properties which can interpret the missing FPs even though the noise is distributed on other FPs.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.38-46
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• 2008

Key-frame selection algorithm is defined as the process of selecting a necessary images for 3D reconstruction from the uncalibrated images. Also, camera calibration of images is necessary for 3D reconstuction. In this paper, we propose a new method of Key-frame selection with the minimal error for camera calibration. Using the full-auto-calibration, we estimate camera parameters for all selected Key-frames. We remove the false matching using the fundamental matrix computed by algebraic deviation from the estimated camera parameters. Finally we obtain 3D reconstructed data. Our experimental results show that the proposed approach is required rather lower time costs than others, the error of reconstructed data is the smallest. The elapsed time for estimating the fundamental matrix is very fast and the error of estimated fundamental matrix is similar to others.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1361-1366
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• 2006

본 논문에서는 제약되지 않은 카메라에서 얻어진 회전과 크기 변화를 가진 영상들을 특징 기반의 보로노이 거리 매칭 방법을 이용하여 고속으로 합성 하는 기법에 관해 기술한다. 기존의 특징점 기반 매칭 기법들이 사람의 개입에 의해 영상을 정합하거나, 크기나 회전 변화를 고려하지 않은 형태의 영상들을 처리하는 것과 달리 회전이나 크기변화요소가 포함된 입력영상들을 사람의 개입이 없이 자동으로 정확한 중첩영역을 빠르게 검색하는 방법을 제안한다. 제안된 방법은 우선 영상내의 특징 점들의 위상 정보와 특징 점들 사이의 거리 정보를 가지는 보로노이 거리 정합법을 통해 대응점을 구하고, 찾아진 대응 쌍들을 이용하여 2차원 투영의 초기 변환행렬을 구한다. 다음으로 비선형 이승오차 최적화 알고리즘을 이용하여 최적의 변환 행렬을 구한 후, 마지막으로 구해진 변환 행렬을 이용하여 영상을 합성한다. 실험결과를 통해 본 논문에서 제안한 방법의 효율성을 보인다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.16-22
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• 2011

Recently, the use of portable projector expands applications to meeting at fields. Accordingly, the projection is not always guaranteed on white screen, causing some color distortion. Several algorithms have been suggested to correct the projected color on the light colored screen. These have limitation on the use of measurement equipment which can't bring always. In this paper, color correction method using general still camera as convenient measurement equipment is proposed to match the colors between on white and colored screens. A patch containing 9 ramps of each channel are firstly projected on white and colored screens, then captured by the camera, respectively, Next, digital values are obtained by the captured image for each ramp patch on both screens, resulting in different values to the same patch. After that, we check which ramp patch on colored screen has the same digital value on white screen, repeating this procedure for all ramp patches. The difference between corresponding ramp patches reveals the quantity of color shift. Then, color correction matrix is obtained by regression method using matched values. In the experimental results, the proposed method gives better color correction on the objective and subjective evaluation than the previous methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.264-266
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• 2019

드론에 프로젝터를 탑재한 드론 프로젝터 시스템을 활용한 이동형 프로젝션 디스플레이를 사용할 경우, 드론의 비행시 발생하는 흔들림이 그대로 프로젝터에 전달되기 때문에 프로젝터에 의해 투영된 영상에 왜곡이 발생하게 된다. 본 논문에서는 종래에 사용되던 드론의 비행정보 기반 투영영상 변환행렬을 실제 영상에 적용해보고 비행 움직임에 의해 발생하는 실제 투영영상에서 발생하는 오차를 평가하기 위한 방법을 제안한다.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.933-941
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• 2010

Biplot is a modern graphical methodology allowing for the projection of high-dimensional data to a low-dimensional subspace that is rich in information on variation in the data, correlation among variables as well as class separation. For the construction of biplots, we use a BiplotGUI package in a free statistical software R with increasing popularity. Moreover, using data from questionnaires given to Chonbuk National University freshmen in 2009, the relationship between career goals and career maturity are studied by applying the biplot method.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.99-106
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• 2016

In this paper, we will discuss about correction method of missing data on noisy observation matrix and uncertainty analysis for the potential noise. In situations without missing data in an observation matrix, this solution is known to be accurately induced by SVD (Singular Value Decomposition). However, usually the several entries of observation matrix have not been observed and other entries have been perturbed by the influence of noise. In this case, it is difficult to find the solution as well as cause the 3D reconstruction error. Therefore, in order to minimize the 3D reconstruction error, above all things, it is necessary to correct reliably the missing data under noise distribution and to give a quantitative evaluation for the corrected results. This paper focuses on a method for correcting missing data using geometrical properties between 2D projected object and 3D reconstructed shape and for estimating a noise level of the observation matrix using ranks of SVD in order to quantitatively evaluate the performance of the correction algorithm.