• 융합신호처리학회논문지
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• 제2권4호
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• pp.16-21
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• 2001

본 논문에서는 2매의 2차원 얼굴영상으로부터 이들의 합성하여 3차원 얼굴의 가상형상을 복원한다. 여기서 2매의 2차원 얼굴영상은 정면과 측면 영상을 사용한다. 임의의 일반 얼굴에 대한 기준모델을 정하고 이 모델에서 얼굴형상의 특징을 표현하는 귀 , 눈 코 및 입 부분에 집중적으로 특징 점을 규정한다. 그 이외에 이마 및 턱부분에도 특징 점을 지정하여 그 위치 좌표를 저장해 둔다. 그 후 정면 영상의 좌 우측에 측면영상을 대칭적으로 접속하고 영상의 기하 변환방법을 적용하여 점차적으로 합성한다. 합성을 효과적으로 처리하기 위해 측면 영상을 정면 영상에 정합될 수 있도록 기하변환을 이용한다. 이 때 나타나는 합성부분에 색상 및 명도의 차를 제거하기 위해 스므딩필터(3$\times$3 화소의 마스크)를 적용하여 자연스런 3차원 가상얼굴을 구현하게 된다. 그 결과 불특정 얼굴형상도 3차원으로 구현할수 있음을 확인하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2002년도 춘계종합학술대회
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• pp.134-138
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• 2002

The human faces do not have distinct features unlike other general objects. In general the features of eyes, nose and mouth which are first recognized when human being see the face are defined. These features have different characteristics depending on different human face. In this paper, We propose a face recognition algorithm using the hidden Markov model(HMM). In the preprocessing stage, we find edges of a face using the locally adaptive threshold scheme and extract features based on generic knowledge of a face, then construct a database with extracted features. In training stage, we generate HMM parameters for each person by using the forward-backward algorithm. In the recognition stage, we apply probability values calculated by the HMM to input data. Then the input face is recognized by the euclidean distance of face feature vector and the cross-correlation between the input image and the database image. Computer simulation shows that the proposed HMM algorithm gives higher recognition rate compared with conventional face recognition algorithms.

• Archives of Plastic Surgery
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• 제37권4호
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• pp.351-360
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• 2010

Purpose: As the influence of mass media increases, the general standard of attractiveness or beauty of a face also changes. The primary purpose of the study is to find out the factors of the attractive and beautiful face recognized by public. Methods: We picked out standard model photography and operated with Adobe$^{(R)}$ Photoshop$^{(R)}$ and Monariza$^{(R)}$ virtual plastic surgery program. The contour of face, eye, nose, forehead, zygoma, chin and proportion of upper, middle, lower face were changed. The interview survey was conducted through structured standard photo for 310 respondents. That was utilized in the final analysis. Multiple regression analysis was executed by SPSS 12.0. It was used to deal with statistical data and all the other necessary analysis. Results: According to general characteristics of the respondents, many differences were found in preferred face and facial aesthetic subunits. The younger generation preferred the lozenge and inverted triangle shape contour. The respondents over 40 of age preferred the egg shape contour. In chin and zygoma contour, the respondents at the age of 20 preferred distinctly small chin and relatively small lower face. On the other hand, the respondents over 40 of age preferred the wide zygoma relatively. In the proportion of upper, middle, lower face, 51.0% of respondents answered 1 : 1 : 1. If they want to have an aesthetic operation, they preferred protruding forehead. Also they preferred the small chin and V-shaped chin in frontal view. Conclusion: Many respondents preferred to have a plastic surgery for the better facial subunit. The statistical evidence from this study suggests that the harmony and balance of facial aesthetic subunits make attractive and beautiful face.

• 디지털산업정보학회논문지
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• 제12권4호
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• pp.107-114
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• 2016

Recently, 3D related technology has become a hot topic for IT. 3D technologies such as 3DTV, Kinect and 3D printers are becoming more and more popular. According to the flow of the times, the goal of this study is that the general public is exposed to 3D technology easily. we have developed a web-based application program that enables 3D modeling of facial front and side photographs using a mobile phone. In order to realize 3D modeling, two photographs (front and side) are photographed with a mobile camera, and ASM (Active Shape Model) and skin binarization technique are used to extract facial height such as nose from facial and side photographs. Three-dimensional coordinates are generated using the face extracted from the front photograph and the face height obtained from the side photograph. Using the 3-D coordinates generated for the standard face model modeled with the standard face as a control point, the face becomes the face of the subject when the RBF (Radial Basis Function) interpolation method is used. Also, in order to cover the face with the modified face model, the control point found in the front photograph is mapped to the texture map coordinate to generate the texture image. Finally, the deformed face model is covered with a texture image, and the 3D modeled image is displayed to the user.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 1999년도 가을 학술발표회 논문집
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• pp.193-200
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• 1999

Since Broms and Bennermark(1967) suggested the face stability criterion based on laboratory extrusion tests and field observations, the face stability of a tunnel driven in cohesive material has been studied by several authors. And recently, more general solution for the tunnel front is given by Leca and Panet(1988). They adopted a limit state design concept to evaluate the face stability of a shallow tunnel driven into cohesionless material and showed that the calculated upper bound solution represented the actual behavior reasonably well. In this study, two factors are simultaneously considered for assessing tunnel face stability: One is the effective stress acting on the tunnel front calculated by upper bound solution; and the other is the seepage force calculated by numerical analysis under the condition of steady state ground water flow. The model tests were performed to evaluate the seepage force acting on the tunnel front and these results were compared with results of numerical analysis. Consequently, the methodology to evaluate the stability of a tunnel face including limit analysis and seepage analysis is suggested under the condition of steady state ground water flow.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2002년도 춘계학술발표논문집 (상)
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• pp.647-650
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• 2002

The human faces do not have distinct features unlike other general objects. In general the features of eyes, nose and mouth which are first recognized when human being see the face are defined. These features have different characteristics depending on different human face. In this paper, We propose a face recognition algorithm using the hidden Markov model(HMM). In the preprocessing stage, we find edges of a face using the locally adaptive threshold scheme and extract features based on generic knowledge of a face, then construct a database with extracted features. In training stage, we generate HMM parameters for each person by using the forward-backward algorithm. In the recognition stage, we apply probability values calculated by the HMM to input data. Then the input face is recognized by the euclidean distance of face feature vector and the cross-correlation between the input image and the database image. Computer simulation shows that the proposed HMM algorithm gives higher recognition rate compared with conventional face recognition algorithms.

• 대한전자공학회논문지SP
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• 제45권6호
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• pp.38-43
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• 2008

피부색 정보는 컬러영상에 포함된 얼굴영역을 검출하는 중요한 요소이다. 피부색 정보로 부터 생성된 통계 피부색 모델을 이용하여 얼굴영역을 검출할 수 있다. 하지만 다른 피부색 부분이 포함되어 있는 컬러영상에서는 일반적인 통계 피부색 모델만으로 정확한 얼굴영역 검출을 할 수 없는 단점을 가진다. 본 논문에서는 다른 피부색 부분이 포함되어 있는 다양한 컬러 영상에서 얼굴영역만을 정확히 검출하기 위한 방법을 제안한다. 제안된 방법은 YCbCr 피부 컬러 모델기반의 피부색 가우시안 분포를 적용하여 얼굴 후보영역 설정 하였고, 영상내의 잡음 부분과 얼굴 영역이외의 부분을 제거하기 위해 수학적 형태학을 적용하였다. 그리고 Haar-like 특성을 이용하여 정확한 얼굴 검출을 수행하였다. 모의실험 결과 제안된 방법이 목이나 팔과 같이 유사한 피부색을 포함한 영상과 다양한 크기의 영상에서도 효과적인 얼굴영역 검출하는 우수함을 보였다.

• 한국철도학회논문집
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• 제16권1호
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• pp.47-51
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• 2013

본 논문은 연약지반 쉴드 TBM 축소 모형실험을 통하여 슬러리에 의해 가해지는 막장 지보압의 변화에 따른 터널 막장면 안정성 변화 양상을 파악하고자 토피고에 따라 0.5D, 0.75D, 1.0D, 1.25D, 1.5D의 총 5개 Case에 대하여 모형실험을 수행하였으며, 이론적인 터널 막장면 지보압 및 모형실험으로 선정된 적정 지보압 값을 상호 비교하였다. 암반 쉴드 TBM과 달리 연약지반 쉴드 TBM의 경우 균질한 지반조건임에 따라 모형실험으로부터 산정된 적정 지보압이 터널 심도에 따른 막장면 토압 및 수압으로부터 이론적으로 산정된 막장압 범위($P_{min}{\leq}P_{slurry\;pressure}{\leq}P_{max}$)와 잘 일치하고 있음을 확인하였다.

• 스마트미디어저널
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• 제7권4호
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• pp.61-69
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• 2018

Multi-tracking of general objects and specific faces is an important topic in the field of computer vision applicable to many branches of industry such as biometrics, security, etc. The rapid development of deep neural networks has resulted in a dramatic improvement in face recognition and object detection problems, which helps improve the multiple-face tracking techniques exploiting the tracking-by-detection method. Our proposed method uses face detection trained with a head dataset to resolve the face deformation problem in the tracking process. Further, we use robust face features extracted from the deep face recognition network to match the tracklets with tracking faces using Hungarian matching method. We achieved promising results regarding the usage of deep face features and head detection in a face tracking benchmark.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.2171-2185
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• 2020

In order to judge that whether the vehicles in different images which are captured by surveillance cameras represent the same vehicle or not, we proposed a novel vehicle face recognition algorithm based on improved Nonnegative Matrix Factorization (NMF), different from traditional vehicle recognition algorithms, there are fewer effective features in vehicle face image than in whole vehicle image in general, which brings certain difficulty to recognition. The innovations mainly include the following two aspects: 1) we proposed a novel idea that the vehicle type can be determined by a few key regions of the vehicle face such as logo, grille and so on; 2) Through adding weight, sparseness and classification property constraints to the NMF model, we can acquire the effective feature bases that represent the key regions of vehicle face image. Experimental results show that the proposed algorithm not only achieve a high correct recognition rate, but also has a strong robustness to some non-cooperative factors such as illumination variation.