• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.303-304
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• 2012

• Journal of Sasang Constitutional Medicine
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• v.19 no.2
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• pp.30-39
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• 2007

1. Objectives The Face is an important standard for the classification of Sasang Constitution. We are developing 3D Automatic Face Recognition Apparatus(3D-AFRA) to analyse the facial characteristics. This apparatus show us 3D image and data of man's face and measure facial figure data. So we should examine the figure restoration error of 3D Automatic Fare Recognition Apparatus(3D-AFRA) in hardware Error Analysis. 2. Methods We scanned Face status by using 3D Automatic Face Recognition Apparatus(3D-AFRA). And also we scanned Face status by using laser scanner(vivid 9i). We compared facial shape data be restored by 3D Automatic Face Recognition Apparatus(3D-AFRA) with facial shape data that be restorated by 3D laser scanner. And we analysed the average error and the maximum error of two data. 3. Results and Conclusions In frontal face, the average error was 0.48mm. and the maximum error was 4.60mm. In whole face, the average error of was 0.99mm. And the maximum error was 6.64mm. In conclusion, We assessed that accuracy of 3D Automatic Face Recognition Apparatus(3D-AFRA) is considerably good.

• The KIPS Transactions:PartB
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• v.18B no.1
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• pp.21-28
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• 2011

A 3D face shape derived from 2D images may be useful in many applications, such as face recognition, face synthesis and human computer interaction. To do this, we develop a fast 3D Active Appearance Model (3D-AAM) method using depth estimation. The training images include specific 3D face poses which are extremely different from one another. The landmark's depth information of landmarks is estimated from the training image sequence by using the approximated Jacobian matrix. It is added at the test phase to deal with the 3D pose variations of the input face. Our experimental results show that the proposed method can efficiently fit the face shape, including the variations of facial expressions and 3D pose variations, better than the typical AAM, and can estimate accurate 3D face shape from images.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.212-227
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• 2008

Since 3D face can be rotated freely in 3D space and illumination effects can be modeled properly, 3D face modeling Is more precise and realistic in face pose, illumination, and expression than 2D face modeling. Thus, 3D modeling is necessitated much in face recognition, game, avatar, and etc. In this paper, we propose a 3D face modeling method based on 3D morphable shape modeling. The proposed 3D modeling method first constructs a 3D morphable shape model out of 3D face scan data obtained using a 3D scanner Next, the proposed method extracts and matches feature points of the face from 2D image sequence containing a face to be modeled, and then estimates 3D vertex coordinates of the feature points using a factorization based SfM technique. Then, the proposed method obtains a 3D shape model of the face to be modeled by fitting the 3D vertices to the constructed 3D morphable shape model. Also, the proposed method makes a cylindrical texture map using 2D face image sequence. Finally, the proposed method builds a 3D face model by rendering the 3D face shape model with the cylindrical texture map. Through building processes of 3D face model by the proposed method, it is shown that the proposed method is relatively easy, fast and precise than the previous 3D face model methods.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1695-1700
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• 2005

In this paper, 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 surface voxel of photo-consistency with inside voxel on the optic ray of the center camera. As iterating the process of the voxels, the threshold value 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 cut as compare with conventional algorithms.

• Korean Journal of Bronchoesophagology
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• v.1 no.1
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• pp.82-93
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• 1995

Three-dimensional reconstruction of computed tomographic image(3D CT) is a well-established imaging modality which has been investigated in various clinical settings. It is commonly performed in case of congenital or developmental abnormalities, and traumatic fracture of skull and face that requires reconstruction of osseous structure. However reporting the 3D CT in laryngeal or tracheal stenosis is rare and its results are obscure. The authors performed 3D CT in six cases of tracheal stenosis and found diagnostic value of 3D CT. A Comparision of diagnostic information obtained from plain X-ray, 2D CT and 3D CT has performed in total six cases of tracheal stenosis. Surgical treatment of the tracheal stenosis was following in these cases : tracheal end to end anastomosis In 1 case, laryngotracheal end to end anastomosis in 2 cases. 3D CT information was compared with operative finding. In two of six cases, satisfactory information was not obtained from 3D CT in evaluating an exact stenosis of trachea. Future, it will be helped in evaluating of tracheal stenosis by 3D CT.

• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.565-574
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• 1999

In reverse engineering area, it is rapidly developing reconstruction of surfaces from scanning or digitizing data, but geometric models of existing objects unavailable many industries. This paper describes new methodology of reverse engineering area, good strategies and important algorithms in reverse engineering area. Furthermore, proposing reconstruction of surface technique is presented. A method find base geometry and blending surface between them. Each based geometry is divided by triangular patch which are compared their normal vector for face grouping. Each group is categorized analytical surface such as a part of the cylinder, the sphere, the cone, and the plane that mean each based geometry surface. And then, each based geometry surface is implemented infinitive surface. Infinitive average surface's intersections are trimmed boundary representation model reconstruction. This method has several benefits such as the time efficiency and automatic functional modeling system in reverse engineering. Especially, it can be applied 3D scanner and 3D copier.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3782-3796
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• 2020

A three-dimensional (3D) reconstruction is an important research area in computer vision. The ability to detect and match features across multiple views of a scene is a critical initial step. The tracking matrix W obtained from a 3D reconstruction can be applied to structure from motion (SFM) algorithms for 3D modeling. We often fail to generate an acceptable number of features when processing face or medical images because such images typically contain large homogeneous regions with minimal variation in intensity. In this study, we seek to locate sufficient matching points not only in general images but also in face and medical images, where it is difficult to determine the feature points. The algorithm is implemented on an adaptive threshold value, a scale invariant feature transform (SIFT), affine SIFT, speeded up robust features (SURF), and affine SURF. By applying the algorithm to face and general images and studying the geometric errors, we can achieve quasi-dense matching points that satisfy well-functioning geometric constraints. We also demonstrate a 3D reconstruction with a respectable performance by applying a column space fitting algorithm, which is an SFM algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.412-417
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• 2015

Kinect sensor has two output data which are produced from red green blue (RGB) sensor and depth sensor, it is called color image and depth map, respectively. Although this device's prices are cheapest than the other devices for three-dimensional (3D) reconstruction, we need extra work for reconstruct a smooth 3D data and also have semantic meaning. It happened because the depth map, which has been produced from depth sensor usually have a coarse and empty value. Consequently, it can be make artifact and holes on the surface, when we reconstruct it to 3D directly. In this paper, we present a method for solving this problem by using implicit surface representation. The key idea for represent implicit surface is by using radial basis function (RBF) and to avoid the trivial solution that the implicit function is zero everywhere, we need to defined on-surface point and off-surface point. Based on our simulation results using captured face as an input, we can produce smooth 3D face and fill the holes on the 3D face surface, since RBF is good for interpolation and holes filling. Modified anisotropic diffusion is used to produced smoothed surface.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.10
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• pp.593-602
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• 2004

A new surface reconstruction scheme for approximating the surface from a set of unorganized 3D points is proposed. Our method, called shrink-wrapped boundary face (SWBF) algorithm, produces the final surface by iteratively shrinking the initial mesh generated from the definition of the boundary faces. Proposed method surmounts the genus-0 spherical topology restriction of previous shrink-wrapping based mesh generation technique, and can be applicable to any kind of surface topology. Furthermore, SWBF is much faster than the previous one since it requires only local nearest-point-search in the shrinking process. According to experiments, it is proved to be very robust and efficient for mesh generation from unorganized points cloud.