• Journal of Digital Contents Society
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• v.9 no.4
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• pp.751-758
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• 2008

The purpose of this study is to implement 3D Face Model, which resembles a user, using 3D Graphic techniques. The implemented 3D Face model is used to further study and implement 3D Facial Aesthetic Surgery System, that can be used to increase the satisfaction rate of patient by comparing before and after facial aesthetic surgery. For designing and implementing 3D Facial Aesthetic Surgery System, 3D Modeling, Texture Mapping for skin, Database system for facial data are studied and implemented independently. The Detailed Adjustment System is, also, implemented for reflecting the minute description of face. The implemented 3D Facial Aesthetic Surgery System for this paper shows more accuacy, convenience, and satisfaction in compare with the existing system.

• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.31-40
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• 2012

In this paper, we propose a method of synthesizing faces of a user and an animation character using a 3D face model. The suggested method first receives two orthogonal 2D face images and extracts major features of the face through the template snake. It then generates a user-customized 3D face model by adjusting a generalized face model using the extracted facial features and by mapping texture maps obtained from two input images to the 3D face model. Finally, it generates a user-customized animation character by synthesizing the generated 3D model to an animation character reflecting the position, size, facial expressions, and rotational information of the character. Experimental results show some results to verify the performance of the suggested algorithm. We expect that our method will be useful to various applications such as games and animation movies.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.929-930
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• 2008

To develop reliable 3D face recognition system, many researchers also have focused on 3D face data acquisition system. Previous many 3D face acquisition systems use visible patterns to solve corresponding problem, and this pattern made anyone who wants to be verified uncomfortable. In this paper, we propose a new invisible infrared line-laser pattern for 3D face data acquisition.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.84-90
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• 2014

This paper presents the results of three-dimensional face point cloud smoothing based on a modified anisotropic diffusion method. The focus of this research was to obtain a 3D face point cloud with a smooth texture and number of vertices equal to the number of vertices input during the smoothing process. Different from other methods, such as using a template D face model, modified anisotropic diffusion only uses basic concepts of convolution and filtering which do not require a complex process. In this research, we used 6D point cloud face data where the first 3D point cloud contained data pertaining to noisy x-, y-, and z-coordinate information, and the other 3D point cloud contained data regarding the red, green, and blue pixel layers as an input system. We used vertex selection to modify the original anisotropic diffusion. The results show that our method has improved performance relative to the original anisotropic diffusion method.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2000-2003
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• 2003

This paper presents a three-dimensional (3D) head pose estimation algorithm for robust face recognition. Given a 3D input image, we automatically extract several important 3D facial feature points based on the facial geometry. To estimate 3D head pose accurately, we propose an Error Compensated-SVD (EC-SVD) algorithm. We estimate the initial 3D head pose of an input image using Singular Value Decomposition (SVD) method, and then perform a Pose refinement procedure in the normalized face space to compensate for the error for each axis. Experimental results show that the proposed method is capable of estimating pose accurately, therefore suitable for 3D face recognition.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.2
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• pp.247-264
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• 2023

Objectives: The study was to examine the features of three-dimensional(3D) face dimensions and to develop fit test panels for the labor population using respirators in South Korea. Methods: This study was part of the first-year work of a two-year-project conducted at Occupational Safety and Health Research Institute in 2021. After 3D head dimensions data were collected from Size Korea Center managing Sixth Size Korea databases, 3D face dimensions DB for the South Korean labor population was established for 21 items of face dimensions in line with the ISO/TS 16976-2 and KS A ISO 15535. With the South Korean labor population 3D face dimensions DB, in accordance with the ISO/TS 16976-2, the descriptive statistics of 3D face dimensions were calculated and two fit test panels were developed. Results: A total of 2,752 subjects were finally determined and they were 52.9% for male, 41.2% for the highest age-group of 15-29, and residents in the capital area. Mean and standard deviation were obtained for each of the 21 3D face dimensions items for the South Korean labor population. Among the items, male and female face widths were 137.6±5.7 mm, 133.2±5.0 mm, respectively. Male and female face lengths were 116.6±7.0 mm, 107.8±6.8 mm, respectively. Two new South Korean fit test panels, a bivariate test panel and a principal component analysis test panel, were developed using the 3D face dimensions DB as well. Conclusions: Using the 3D face dimensions DB, the mean and standard deviation were featured for each of the 21 items and also the two fit test panels were newly developed in the study. It is suggested that the study outputs should be utilized practically and effectively in selection, use, and management of respirators at work, expecting that respiratory protection can be furthermore improved for respirator users including labor population across the country.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.714-718
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• 2009

3D reconstruction of a human face from an image sequence remains an important problem in computer vision. We propose a method, based on a factorization algorithm, that reconstructs a 3D face model from short image sequences exhibiting rotational motion. Factorization algorithms can recover structure and motion simultaneously from one image sequence, but they usually require that all feature points be well tracked. Under rotational motion, however, feature tracking often fails due to occlusion and frame out of features. Additionally, the paucity of images may make feature tracking more difficult or decrease reconstruction accuracy. The proposed 3D reconstruction approach can handle short image sequences exhibiting rotational motion wherein feature points are likely to be missing. We implement the proposal as a reconstruction method; it employs image sequence division and a feature tracking method that uses Active Appearance Models to avoid the failure of feature tracking. Experiments conducted on an image sequence of a human face demonstrate the effectiveness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.103-110
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• 2011

A widely used 3D face reconstruction method, structure from motion(SfM), shows robust performance when frontal, left, and right face images are used. However, this method cannot reconstruct a self-occluded facial part correctly when only one side view face images are used because only partial facial feature points can be used in this case. In order to solve the problem, the proposed method exploit a constrain that is bilateral symmetry of human faces in order to generate bilateral facial feature points and use both input facial feature points and generated facial feature points to reconstruct a 3D face. For quantitative evaluation of the proposed method, 3D faces were obtained from a 3D face scanner and compared with the reconstructed 3D faces. The experimental results show that the proposed 3D face reconstruction method based on both facial feature points outperforms the previous 3D face reconstruction method based on only partial facial feature points.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.53-62
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• 2011

In this paper, high-tech IT Convergence, to the development of complex technology, special technology, video object recognition technology was considered only as a smart - phone technology with the development of personal portable terminal has been developed crossroads. Technology-based detection of 3D face recognition technology that recognizes objects detected through the intelligent video recognition technology has been evolving technologies based on image recognition, face detection technology with through the development speed is booming. In this paper, based on human face recognition technology to detect the object recognition image processing technology is applied through the face recognition technology applied to the IP camera is the party of the mouth, and allowed the ability to identify and apply the human face recognition, measurement techniques applied research is suggested. Study plan: 1) face model based face tracking technology was developed and applied 2) algorithm developed by PC-based measurement of human perception through the CPU load in the face value of their basic parameters can be tracked, and 3) bilateral distance and the angle of gaze can be tracked in real time, proved effective.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.1
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• pp.47-52
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• 2010

In this paper, we introduce a new approach for real-time 3D face pose discrimination based on active IR illumination from a monocular view of the camera. Under the IR illumination, the pupils appear bright. We develop algorithms for efficient and robust detection and tracking pupils in real time. Based on the geometric distortions of pupils under different face orientations, an eigen eye feature space is built based on training data that captures the relationship between 3D face orientation and the geometric features of the pupils. The 3D face pose for an input query image is subsequently classified using the eigen eye feature space. From the experiment, we obtained the range of results of discrimination from the subjects which close to the camera are from 94,67%, minimum from 100%, maximum.