• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.305-309
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• 2006

In this paper, a face recognition algorithm system using Principle Component Analysis is proposed. The algorithm recognized a person by comparing characteristics (features) of the face to those of known individuals which is a face database of Intelligence Control Laboratory(ICONL). Experiments were simulated in order to demonstrate the performance of this algorithm due to face recognition which presented for the classification of face and non-face and the classification of known and unknown.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.91-103
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• 2022

Purpose: After COVID-19, changes in the educational ecosystem take place and fire service academy education system have shifted from face-to-face into non fact-to-face. So, the educational effect of fire officials is decreased and the satisfaction level is also decreased. In this study, we want to examine the current status of non-face-to-face real-time remote education and supplement the problems to improve the educational methods, the educational environment, etc. Method: This study is an independent variable that affects non-face-to-face real-time remote education, consisting of education system environment, self-efficacy of computers, contents (education contents, structure, design, etc.), and proper interaction. A dependent variable was selected with satisfaction for non-face-to-face real-time remote education. In addition, it was selected and analyzed as an active property of learning motivation and learning attitude as control variables. Result: The better the content and the more active the learning motivation and the attitude toward learning, the higher the satisfaction of non-face-to-face real-time remote education, and the more active the learning motivation and the attitude toward learning, the more positive the computer self-efficacy and the satisfaction of learning Conclusion: In order to increase the satisfaction of non-face-to-face real-time education due to COVID-19, education designers or professors need to provide non-face-to-face education contents that can increase the aggressiveness of their learning motivation and learning attitude, and to increase the satisfaction of education for learners by increasing computer self-efficacy through pre-education of non-face-to-face education systems.

• The Korean Society of Law and Medicine
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• v.23 no.3
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• pp.47-87
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• 2022

Due to the COVID-19 pandemic, non-face-to-face treatment was temporarily permitted. A lot of consensus has been formed on the need to continuous non-face-to-face treatment. However, the current 「Medical Service Act」 only permits telemedicine between doctors and medical personnel. On the other hand, as a result of legal interpretation, there is an opinion that non-face-to-face treatment is allowed. But considering the overall legal system, non-face-to-face treatment is not allowed. Nevertheless, we have to consider the reality such as the development of science and technology and the outbreak of infectious diseases. Therefore, it is not advisable to allow face-to-face treatment only. Ultimately, it is necessary to find ways to ensure that non-foce-to-face treatment can be performed in a safe and effective manner. And it should be institutionalized. This is strategically necessary and important. Therefore, we must look over ahead legal issues to be discussed. First of all, the scope, the target disease and the subject of implement have to be clear. Also, structurally, the standards of facilities and equipment must be prepared for non-face-to-face treatment to be implemented. Functionally, communication and information exchange between doctors and patients should be well conducted. In addition, the information protection management system that occurs in the process of non-face-to-face treatment should be materialized. Lastly, the issue of responsibility and cost of non-face-to-face treatment should be decided in detail. When these problems materialize, it can be expected that a safe non-face-to-face treatment environment will be established.

• Journal of Integrative Natural Science
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• v.9 no.2
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• pp.155-160
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• 2016

Applying image processing techniques to education, the face of the learner is photographed, and expression and movement are detected from video, and the system which estimates degree of concentration of the learner is developed. For one learner, the measuring system is designed in terms of estimating a degree of concentration from direction of line of learner's sight and condition of the eye. In case of multiple learners, it must need to measure each concentration level of all learners in the classroom. But it is inefficient because one camera per each learner is required. In this paper, position in the face region is estimated from video which photographs the learner in the class by the difference between frames within the motion direction. And the system which detects the face direction by the face part detection by template matching is proposed. From the result of the difference between frames in the first image of the video, frontal face detection by Viola-Jones method is performed. Also the direction of the motion which arose in the face region is estimated with the migration length and the face region is tracked. Then the face parts are detected to tracking. Finally, the direction of the face is estimated from the result of face tracking and face parts detection.

• Journal of Korea Multimedia Society
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• v.7 no.2
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• pp.156-163
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• 2004

In this paper, we propose an adaptive face region detection and real-time face identification algorithm using face feature evaluation function. The proposed algorithm can detect exact face region adaptively by using skin color information for races as well as intensity and elliptical masking method. And also, it improves face recognition efficiency using geometrical face feature and geometric evaluation function between features. The proposed algorithm can be used for the development of biometric and security system areas. In the experiment, the superiority of the proposed method has been tested using real image, the proposed algorithm shows more improved recognition efficiency as well as face region detection efficiency than conventional method.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.10
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• pp.1530-1540
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• 2009

Life expectancy has increased and people are more concerned with keeping their 'youth'. Appearance is a competitive edge and people are caught up in a baby face fad that has expanded into a culture and beauty trend. This study examined the definitions and phrenological characteristics of a baby face and the causes of the baby face fad in a review of the baby face as a "sociocultural and beauty cultural code" based on literature, journals, previous papers, and Internet materials. Anatomically speaking, a "baby face" refers to a face that keeps the features of a child's face without aging signs. The baby face fad gained momentum due to the influences of the digital culture, the encouragement of the mass media, changes to the social structure, dietary improvements, new living styles, and an evolving aesthetic sense. The results reveal the sociocultural backgrounds behind the "baby face fad" settling down as a part of culture in addition to the phrenological characteristics of a baby face. It is also estimated that the baby face fad could affect the beauty culture and trends as a social phenomena.

• Korean Journal of Human Ecology
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• v.14 no.5
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• pp.813-820
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• 2005

The beauty itself cannot be changed by the time, but the concept of the beauty can be influence by the time and cultural background. The purpose of this study is to analyze the beautiful faces or ugly faces among the young women and to provide useful guideline to make up for the modem concept of beauty. The facial photographs of 180 adlut women(aged between 20 and 29) in Pusan and Ulsan area were sampled to be measured and classified as the beautiful or ordinary or ugly faces. Data were analyzed by Frequencies, Mean, Duncan's Multiple Range Test. The major results were as followings; the Beautiful face has a relatively small face with a broad forehead and a small lower face. It also has a wide palpebral fissure, narrow intercanthal distance, a narrow nose and a big mouth. Physiognomic face length was 182.38mm, the upper face length was 59.82mm, the middle face length 60.82mm, the lower face length 61.76mm, and the index of face length to face breadth was 1.35. And also the faces within the figures are considered as the beautiful or ordinary or ugly faces from those measurements like face length/bizygion breadth, intercanthal distance, mouth width, upper vermilion height, lower vermilion height.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.223-226
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• 2003

When we detect side-view face in color image, we decide a candidate face region using skin-tone color, and confirm to the face by template matching. Cang Wei use a left and a right template of face, calculate to similarity value by hausdorff method, and decide the final side-view face. It has a characteristic that side-view face is wide spreading neck region. To get exactly result, face region is separated vertically by 3 pixel unit, and matched template. In this paper, we assume that a side-view face is a right side-view or a left side-view face. We separate a half of the candidate face region vertically, and regard a left side as left candidate face, a right side as right candidate face by template matching. This method detect faster than Gang Wei method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.194-199
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• 2009

This paper proposes a face detection algorithm that uses geometrical information on face and hair region. This information that face adjoins hair regions can be the important one for face detection. It is also kept in images with frontal, rotated and lateral face. The face candidates are founded by the analysis of skin regions after detecting the skin and hair color regions in an image. Next, the intersected lesions between face candidates and hair's are created. Finally, the face candidates that include the subsets of these regions turn out to be face. Experimental results showed the high detection rates for frontal and lateral faces as well as faces geometrically distorted.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.1
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• pp.35-41
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• 2017

We propose a face recognition and notification system that can transform visual face information into tactile signals in order to help visually impaired people. The proposed system consists of a glasses type camera, a mobile computer and an electronic cane. The glasses type camera captures the frontal view of the user, and sends this image to mobile computer. The mobile computer starts to search for human's face in the image when obstacles are detected by ultrasonic sensors. In a case that human's face is detected, the mobile computer identifies detected face. At this time, Adaboost and compressive sensing are used as a detector and a classifier, respectively. After the identification procedures of the detected face, the identified face information is sent to controller attached to a cane using a Bluetooth communication. The controller generates motor control signals using Pulse Width Modulation (PWM) according to the recognized face labels. The vibration motor generates vibration patterns to inform the visually impaired person of the face recognition result. The experimental results of face recognition and notification system show that proposed system is helpful for visually impaired people by providing person identification results in front of him/her.