• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.15-18
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• 2008

This paper proposes a method to reconstruct the 3-D face using structured light image. First of all, we suppose that each sight vector of a projector and camera are parallel. We project the structured light in the shape of lattice on the background to acquire the reference-structured light image. This image is used to calibrate the projector and camera. Since then, we acquire the face-structured light image which is projected the same structured light on the face. These two structured light images are used to reconstruct the 3-D face through the variation which is measured from the positional difference of feature vectors. In our experiment result, we could reconstruct the 3-D face image as recognize through these simple devices.

• Journal of Multimedia Information System
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• v.6 no.1
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• pp.15-22
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• 2019

There are many ways to perform face recognition. The first step of face recognition is the face detection step. If the face is not found in the first step, the face recognition fails. Face detection research has many difficulties because it can be varied according to face size change, left and right rotation and up and down rotation, side face and front face, facial expression, and light condition. In this study, facial features are extracted and the extracted features are geometrically reconstructed in order to improve face recognition rate in extracted face region. Also, it is aimed to adjust face angle using reconstructed facial feature vector, and to improve recognition rate for each face angle. In the recognition attempt using the result after the geometric reconstruction, both the up and down and the left and right facial angles have improved recognition performance.

• IE interfaces
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• v.12 no.2
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• pp.205-209
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• 1999

In reverse engineering area, the reconstruction of surfaces from scanned or digitized data is being developed, but geometric model of existing objects is not available in industries. This paper presents the new approach to the reconstruction of surface technique. A proposed methodology finds base geometry and blends surface between them. Each based geometry is divided by tri-angular patches which are compared with their normal vector for face grouping. Each group is categorized analytical surface such as a part of cylinder, sphere and cone, and plane shapes to represent the based geometry surface. And then, each based geometry surface is implemented to the infinitive surface. Infinitive surface's intersections are trimmed by boundary representation model reconstruction. This method has several benefits such as time efficiency and automatic functional modeling system in reverse engineering. Especially, it can be directly applied 3D fax and 3D copier.

• Journal of IKEEE
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• v.26 no.2
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• pp.160-168
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• 2022

In this paper, we propose a 3D mesh reconstruction method from a single image using deep learning and a sphere shape transformation method. The proposed method has the following originality that is different from the existing method. First, the position of the vertex of the sphere is modified to be very similar to the 3D point cloud of an object through a deep learning network, unlike the existing method of building edges or faces by connecting nearby points. Because 3D point cloud is used, less memory is required and faster operation is possible because only addition operation is performed between offset value at the vertices of the sphere. Second, the 3D mesh is reconstructed by covering the surface information of the sphere on the modified vertices. Even when the distance between the points of the 3D point cloud created by correcting the position of the vertices of the sphere is not constant, it already has the face information of the sphere called face information of the sphere, which indicates whether the points are connected or not, thereby preventing simplification or loss of expression. can do. In order to evaluate the objective reliability of the proposed method, the experiment was conducted in the same way as in the comparative papers using the ShapeNet dataset, which is an open standard dataset. As a result, the IoU value of the method proposed in this paper was 0.581, and the chamfer distance value was It was calculated as 0.212. The higher the IoU value and the lower the chamfer distance value, the better the results. Therefore, the efficiency of the 3D mesh reconstruction was demonstrated compared to the methods published in other papers.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.248-251
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• 2007

In this paper, we are propose a method to estimate the 2-D mesh from structured light image for reconstruction of 3-D face image. To acquire the structured light image, we are project structured light on the face using the projector. we are extract the projected cross points from the acquire image. The 2-D mesh image is extracted from the position and angle of cross points. In the extraction processing, the error was fixed to extract the correct 2-D mesh.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.129-135
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• 2022

Real human digital models appear more and more frequently in VR/AR application scenarios, in which real-time markerless face capture animation of personalized virtual human faces is an important research topic. The traditional way to achieve personalized real human facial animation requires multiple mature animation staff, and in practice, the complex process and difficult technology may bring obstacles to inexperienced users. This paper proposes a new process to solve this kind of work, which has the advantages of low cost and less time than the traditional production method. For the personalized real human face model obtained by 3D reconstruction technology, first, use R3ds Wrap to topology the model, then use Avatary to make 52 Blend-Shape model files suitable for AR-Kit, and finally realize real-time markerless face capture 3D real human on the UE4 platform facial motion capture, this study makes rational use of the advantages of software and proposes a more efficient workflow for real-time markerless facial motion capture of personalized 3D real human models, The process ideas proposed in this paper can be helpful for other scholars who study this kind of work.

• Journal of the Optical Society of Korea
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• v.20 no.2
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• pp.239-244
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• 2016

Mugshot face images, routinely collected by police, usually contain both frontal and profile views. Existing automated face recognition methods exploited mugshot databases by enlarging the gallery with synthetic multi-view face images generated from the mugshot face images. This paper, instead, proposes to match the query arbitrary view face image directly to the enrolled frontal and profile face images. During matching, the 3D face shape model reconstructed from the mugshot face images is used to establish corresponding semantic parts between query and gallery face images, based on which comparison is done. The final recognition result is obtained by fusing the matching results with frontal and profile face images. Compared with previous methods, the proposed method better utilizes mugshot databases without using synthetic face images that may have artifacts. Its effectiveness has been demonstrated on the Color FERET and CMU PIE databases.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.6
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• pp.93-100
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• 2005

We propose an optimal thresholding method for the voxel coloring in the reconstruction of a 3D shape. Our purposed method is a new approach to resolve the trade-off error of the threshold value on determining the photo-consistency in the conventional method. Optimal thresholding value is decided to compare the photo-consistency of a surface with inside voxel on the optic ray of the center camera. As iterating the process of the vokels, the threshold is approached to the optimal value for the individual surface voxel. And also, graph cut method is reduced to the surface noise on eliminating neighboring voxel. To verify the proposed algorithm, we simulated in the virtual and real environment. It is advantaged to speed up and accuracy of a 3D face reconstruction by applying the methods of optimal threshold and graph as compare with conventional algorithms.

• Electronics and Telecommunications Trends
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• v.27 no.3
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• pp.12-21
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• 2012

최근 3DTV, 입체 모니터, 입체 노트북 등이 출시되고, 3D 영화, 게임 등 3D 관련 산업이 성장하면서 관련 콘텐츠의 요구사항이 증가하고 있다. 특히, 3D 콘텐츠의 주요 요소 중 하나인 인체는 전통적으로 고가의 3D 스캐너를 이용해 모델링하는 방식을 주로 사용해 왔다. 하지만 근래에는 광학 기술 및 컴퓨팅 성능의 향상으로 구조광과 같은 능동 센서나 카메라로부터 획득한 영상을 기반으로 3D 인체 외형을 복원하는 연구가 각광을 받고 있다. 이런 추세에 발맞춰 본고에서는 인체 중에서도 사용자의 민감도가 높은 얼굴의 3D 복원 기술 및 연구 동향을 살펴보고, 다양한 응용을 목적으로 ETRI에서 개발 중인 3D 얼굴 복원 기술을 소개하고자 한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.212-214
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• 2021

In a society with Covid-19 as part of our daily lives, we had to adapt ourselves to a new reality to maintain our lifestyles as normal as possible. An example of this is teleworking and online classes. However, several issues appeared on the go as we started the new way of living. One of them is the doubt of knowing if real people are in front of the camera or if someone is paying attention during a lecture. Therefore, we encountered this issue by creating a 3D reconstruction tool to identify human faces and expressions actively. We use a web camera, a lightweight 3D face model, and use the 2D facial landmark to fit expression coefficients to drive the 3D model. With this Model, it is possible to represent our faces with an Avatar and fully control its bones with rotation and translation parameters. Therefore, in order to reconstruct facial expressions during online meetings, we proposed the above methods as our solution to solve the main issue.