• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.499-501
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• 2001

본 논문에서는 사실적인 아바타(avata) 구현의 핵심이라 할 수 있는 입체적인 얼굴 표현을 위해, (※원문참조) 기하학적인 정보를 사용하지 않고 중첩 메쉬를 허용하는 개선된 메쉬 워프 알고리즘(mesh warp algor※원문참조)을 이용하여 IBR(Image Based Rendering)을 구현하는 방법을 제안한다. 3차원 모델을 대신하기 위해 (※원문참조) 인물의 정면, 좌우 반측면, 좌우 측면의 얼굴 영상들에 대해 작성된 메쉬를 사용한다. 합성하고자 하는 (※원문참조) 정면 얼굴 영상에 대해서는 정면 메쉬만을 작성하고, 반측면이나 측면 메쉬는 표준 메쉬를 근거로 자(※원문참조)된다. 얼굴 포즈 합성의 성능을 펴가하기 위해, 얼굴을 수평으로 회전하는 실제 포즈 영상과 합성된 포(※원문참조)에 대해 주요 특징점 들을 정규화 한 위치 오차를 측정한 결과, 평균적으로 양 눈의 중심에서 입의 (※원문참조)리에 대해 약 5%의 위치 오차만이 발생한 것으로 나타났다.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.657-660
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• 2002

컴퓨터그래픽의 급격한 기술 발달과 사용자 층의 다양한 멀티미디어 정보에 대한 요구로 기존의 단순한 2차원 영상 정보는 점차 3차원 정보로 표현되어가고 있고, 사용자의 예술 및 개인 문화에 대한 관심도가 높아지면서 독특한 자신만의 개성을 표현할 수 있는 아바타, 캐리커처와 같은 표현매체에 대한 욕구가 증가하고 있다. 그러나 기존의 펜이나 화필로 그리는 케리커쳐는 예술성, 정교함 그리고 자신만의 독특한 특징적인 개성을 표현 할 수 있는 장점이 있으나 장소, 시간, 인원 등에서 응용성과 확장성이 제한 될 수밖에 없고, 이에 따른 제작비용이나 소요 시간, 노력 등이 많이 소요된다. 본 논문에서는 기존에 수동으로 이루어지고 있는 캐리커쳐를 한 장의 정면 얼굴 이미지를 이용하여 3차원 얼굴 모델을 생성하고, 각 얼굴 영역의 특징 요소를 스플라인으로 표현하여 스플라인의 제어선과 제어점을 조정하여 자동으로 캐리커쳐를 생성하는 시스템을 개발하는데 목적이 있다.

• Journal of Broadcast Engineering
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• v.13 no.3
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• pp.339-349
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• 2008

We present a novel method to estimate the light source direction and relight a face texture image of a single 3D model under arbitrary unknown illumination conditions. We create a virtual irradiance sphere to detect the light source direction from a given illuminated texture image using both normal vector mapping and weighted bilinear interpolation. We then induce a relighting equation with estimated ambient and diffuse coefficients. We provide the result of a series of experiments on light source estimation, relighting and face recognition to show the efficiency and accuracy of the proposed method in restoring the shading and shadows areas of a face texture image. Our approach for face relighting can be used for not only illuminant invariant face recognition applications but also reducing visual load and Improving visual performance in tasks using 3D displays.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.87-95
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• 2006

In this paper, we propose a novel feature extraction method for face recognition, based on Discrete Cosine Transform (DCT), Energy Probability (EP), and Linear Discriminant Analysis (LDA). We define an energy probability as magnitude of effective information and it is used to create a frequency mask in OCT domain. The feature extraction method consists of three steps; i) the spatial domain of face images is transformed into the frequency domain called OCT domain; ii) energy property is applied on DCT domain that acquire from face image for the purpose of dimension reduction of data and optimization of valid information; iii) in order to obtain the most significant and invariant feature of face images, LDA is applied to the data extracted using frequency mask. In experiments, the recognition rate is 96.8% in ETRI database and 100% in ORL database. The proposed method has been shown improvements on the dimension reduction of feature space and the face recognition over the previously proposed methods.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.41-48
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• 2015

Recently, the spread of 3D printers has been increasing the demand for 3D models. However, the creation of 3D models should have a trained specialist using specialized softwares. This paper is about an algorithm to produce a 3D model from a single sheet of two-dimensional front face photograph, so that ordinary people can easily create 3D models. The background and the foreground are separated from a photo and predetermined constant number vertices are placed on the seperated foreground 2D image at a same interval. The arranged vertex location are extended in three dimensions by using the gray level of the pixel on the vertex and the characteristics of eyebrows and nose of the nomal human face. The separating method of the foreground and the background uses the edge information of the silhouette. The AdaBoost algorithm using the Haar-like feature is also employed to find the location of the eyes and nose. The 3D models obtained by using this algorithm are good enough to use for 3D printing even though some manual treatment might be required a little bit. The algorithm will be useful for providing 3D contents in conjunction with the spread of 3D printers.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.839-842
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• 2005

본 논문은 스테레오 카메라를 통해 얻은 변이 정보를 이용하여, 3 차원으로 머리의 회전 각도를 추정하는 방법을 제안한다. 머리 회전에 의한 주시 방향은 사람이 관심을 가지는 방향이므로 이동을 추정하는 것에 비해 많은 중요성을 갖는다. 본 논문에서는 얼굴 영역 내의 여러 특징점들 중 3 개의 특징점들을 포함하는 여러 평면(Plane)이 머리가 이동하더라도, 그 평면들 사이의 각은 변하지 않으므로, 회전 각도 추정에 영향을 주지 않는 점을 이용하여 회전 각도를 추정하였다. 또한, 기존 논문이 카메라 보정을 통해 3 차원 위치를 측정하지만, 제안하는 방법은 변이 공간에서 회전 각도를 추정하기 때문에 카메라 보정 과정이 필요하지 않다. 변이 정보를 얻기 위한 스테레오 장비는 평행 카메라 모델로 가정하며, 얼굴 내의 특징점은 KLT(Kanade-Lucas-Tomasi) 특징 추적 알고리즘을 이용하였다. 실험결과는 기준 영상에 대하여 추정된 3 차원 각도를 나타낸다.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.367-371
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• 2006

Multilayer percepteon has the advantage of learning their optimal parameters and efficiency. However, MLP shows some drawbacks when dealing with high dimensional data within the input space. Also, it Is very difficult to find the optimal parameters when the input data are highly correlated such as large scale face dataset. In this paper, we propose a novel technique for face recognition based on LDA and local MLP. To resolve the main drawback of MLP, we calculate the reduced features by LDA in advance. And then, we construct a local MLP per group consisting of subset of facedatabase to find its optimal learning parameters rather than using whole faces. Finally, we designed the face recognition system combined with the local MLPs. From various experiments, we obtained better classification performance in comparison with the results produced by conventional methods such as PCA and LDA.

• Korean Journal of Cognitive Science
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• v.11 no.2
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• pp.79-87
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• 2000

In this paper we present a face recognition and face detection algorithm in MPEG compressed video. The proposed method consists three stage of processing steps. The first step is to produce a spatially reduced DC image form MPEG compressed video for processing. And the second step is face detection on reduced DC image. Finally, the last step is face recognition on partially extracted compressed frames which contain the detected faces. The spatially reduced DC image is produced from two dimensional inverse DCT of the DC coefficient and the first two AC coefficients. The face detection is performed on DC image and face recognition is performed on one extracted frame per GOP by using the K-L transform. In order to evaluate the proposed method, we carried out experiments on video database. The experiment results show the proposed method is very efficient and helpful for target tasks.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.23-35
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• 2002

Gaze detection is to locate the position on a monitor screen where a user is looking. In our work, we implement it with a computer vision system setting a single camera above a monitor and a user moves (rotates and/or translates) his face to gaze at a different position on the monitor. To detect the gaze position, we locate facial region and facial features(both eyes, nostrils and lip corners) automatically in 2D camera images. From the movement of feature points detected in starting images, we can compute the initial 3D positions of those features by camera calibration and parameter estimation algorithm. Then, when a user moves(rotates and/or translates) his face in order to gaze at one position on a monitor, the moved 3D positions of those features can be computed from 3D rotation and translation estimation and affine transform. Finally, the gaze position on a monitor is computed from the normal vector of the plane determined by those moved 3D positions of features. As experimental results, we can obtain the gaze position on a monitor(19inches) and the gaze position accuracy between the computed positions and the real ones is about 2.01 inches of RMS error.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.63-69
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• 2004

This paper proposes a novel method for achieving pose-invariant face recognition using cylindrical model. On the assumption that a face is shaped like that of a cylinder, we estimate the object's pose and then extract the frontal face image via a pose transform with previously estimated pose angle. By employing the proposed pose transform technique we can increase the face recognition performance using the frontal face images. Through representative experiments, we achieved an increased recognition rate from 61.43% to 94.76% by the pose transform. Additionally, the recognition rate with the proposed method achieves as good as that of the more complicated 3D face model.