• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05a
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• pp.106-109
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• 2004

Many reported methods assume that the faces in an image or an image sequence have been identified and localization. Face detection from image is a challenging task because of variability in scale, location, orientation and pose. In this paper, we present an efficient linear discriminant for multi-view face detection. Our approaches are based on linear discriminant. We define training data with fisher linear discriminant to efficient learning method. Face detection is considerably difficult because it will be influenced by poses of human face and changes in illumination. This idea can solve the multi-view and scale face detection problem poses. Quickly and efficiently, which fits for detecting face automatically. In this paper, we extract face using fisher linear discriminant that is hierarchical models invariant pose and background. We estimation the pose in detected face and eye detect. The purpose of this paper is to classify face and non-face and efficient fisher linear discriminant..

• Journal of Engineering Education Research
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• v.25 no.1
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• pp.22-32
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• 2022

The purpose of this study is to design and operate non-face-to-face online practice class in engineering education, and to explore students' perceptions and effectiveness of them. To this end, after developing and implementing a strategy for non-face-to-face online practice activities in the 'Introduction to Electric Circuits and Lab' course, the questionnaire responses of 47 learners were analyzed, and the group differences were investigated using Kruskal-Wallis test. As a result, it was found that students' perceptions of non-face-to-face online practice class were positive in terms of learning effect, learning convenience, interaction, and satisfaction. The group difference according to the face-to-face/non-face-to-face preference method was found to be higher in the group that preferred non-face-to-face class in terms of learning convenience, interaction and satisfaction. As for the group difference according to the number of questions and answers of the learners, the group who answered the question showed a higher awareness of the learning convenience and interaction than the group that did not. In addition, implications for designing a learning environment for non-face-to-face online practice classes were presented.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1566-1576
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• 2007

Camera pose information from 2D face image is very important for making virtual 3D face model synchronize with the real face. It is also very important for any other uses such as: human computer interface, 3D object estimation, automatic camera control etc. In this paper, we have presented a camera position determination algorithm from a single 2D face image using the relationship between mouth position information and face region boundary information. Our algorithm first corrects the color bias by a lighting compensation algorithm, then we nonlinearly transformed the image into $YC_bC_r$ color space and use the visible chrominance feature of face in this color space to detect human face region. And then for face candidate, use the nearly reversed relationship information between $C_b\;and\;C_r$ cluster of face feature to detect mouth position. And then we use the geometrical relationship between mouth position information and face region boundary information to determine rotation angles in both x-axis and y-axis of camera position and use the relationship between face region size information and Camera-Face distance information to determine the camera-face distance. Experimental results demonstrate the validity of our algorithm and the correct determination rate is accredited for applying it into practice.

• Journal of KIISE:Software and Applications
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• v.32 no.12
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• pp.1247-1259
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• 2005

This paper proposes a real-time face recognition system which detects multiple faces from low resolution video such as web-camera video. Face recognition system consists of the face detection step and the face classification step. At First, it finds face region candidates by using AdaBoost based object detection method which have fast speed and robust performance. It generates reduced feature vector for each face region candidate by using principle component analysis. At Second, Face classification used Principle Component Analysis and multi-SVM. Experimental result shows that the proposed method achieves real-time face detection and face recognition from low resolution video. Additionally, We implement the auto-tracking face recognition system using the Pan-Tilt Web-camera and radio On/Off digital door-lock system with face recognition system.

• Korea Journal of Hospital Management
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• v.28 no.4
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• pp.1-22
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• 2023

Purposes: The purpose of this study is to identify and analyze the factors that affect patients reusing non-face-to-face treatments at tertiary general hospitals. Methodology: We retrospectively analyzed a patient's reuse of non-face-to-face treatment from February 1, 2020, to December 31, 2021, at a tertiary general hospital in Seoul within one year of the first non-face-to-face treatment. A frequency analysis was conducted to identify the study subjects' demographic characteristics, treatment type characteristics, disease characteristics, and hospital use type characteristics. Also, across-analysis was conducted to verify the difference in non-face-to-face treatment reuse according to the characteristics a multiple logistic regression analysis was conducted to identify the factors affecting the reuse of non-face-to-face treatment by non-face-to-face treatment patients. Findings: The results of this study can be interpreted as indicating that the following groups are more likely tore use the non-face-to-face treatment: women, children, the elderly, Patients living far from the hospital, psychiatric patients, pediatric patients, medical benefits recipients, chronic patients, patients with mobility difficulties, and patients with high loyalty to hospitals. Practical Implications: When developing a non-face-to-face treatment system in the future, based on the results of this study, it is possible to target patients who prefer non-face-to-face treatment. And this study will be research material for vitalizing non-face-to-face treatment. In addition, the activation of the non-face-to-face treatment system will be an effective means for improving the quality of medical services and generating profits in hospitals in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.330-337
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• 2005

This paper proposes a method which improves the performance of face detection by using SVM(Support Vector Machine). first, it finds face region candidates by using AdaBoost based object detection method which selects a small number of critical features from a larger set. Next it classifies if the candidate is a face or non-face by using SVM(Support Vector Machine). Experimental results shows that the proposed method improve accuracy of face detection in comparison with existing method.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1015-1016
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• 2008

In this paper, the method which searchs a character of face and transforms it by FACS(Facial Action Coding System) for face modeling is suggested. FACS has a function to build an expression of face to AUs(Action Units) and make various face expressions. The system performs to find accurate Action Units of sample face and use setted AUs. Consequently it carries out the coefficient for transforming face model by 2D AUs matching.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.208-223
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• 2015

To solve the problem of face recognition with complex changes and further improve the efficiency, a new near-infrared face recognition algorithm which fuses E-GV-LBP and FKNN algorithm is proposed. Firstly, it transforms near infrared face image by Gabor wavelet. Then, it extracts LBP coding feature that contains space, scale and direction information. Finally, this paper introduces an improved FKNN algorithm which is based on spatial domain. The proposed approach has brought face recognition more quickly and accurately. The experiment results show that the new algorithm has improved the recognition accuracy and computing time under the near-infrared light and other complex changes. In addition, this method can be used for face recognition under visible light as well.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.992-999
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• 2011

This paper proposed a human body posture recognition program based on haar-like feature and hand activity detection. Its distinguishing features are the combination of face detection and motion detection. Firstly, the program uses the haar-like feature face detection to receive the location of human face. The haar-like feature is provided with the advantages of speed. It means the less amount of calculation the haar-like feature can exclude a large number of interference, and it can discriminate human face more accurately, and achieve the face position. Then the program uses the frame subtraction to achieve the position of human body motion. This method is provided with good performance of the motion detection. Afterwards, the program recognises the human body motion by calculating the relationship of the face position with the position of human body motion contour. By the test, we know that the recognition rate of this algorithm is more than 92%. The results show that, this algorithm can achieve the result quickly, and guarantee the exactitude of the result.

• The Journal of Industrial Distribution & Business
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• v.10 no.5
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• pp.37-47
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• 2019

Purpose - It is well known that chemyon, referred to by Westerners as face, naturally penetrates the daily life of Asians and influences their cognition, emotion, and behavior. Studies related to chemyon have been conducted in marketing and consumer behavior fields (e.g., luxury products or brands, service failure and recovery, brand preferences, consumer decision making, wedding ceremony, gift giving). A bulk of studies demonstrate that chemyon influences consumption behavior in Asian consumers. Although chemyon significantly influences consumption behavior of Asian consumers, it is also a cultural phenomenon that is not completely explained within the Western viewpoint. Whereas a number of researchers have approached cross-cultural studies of Asian and Western consumers, a limited number of studies have examined it from the perspective of chemyom. The purpose of this study is to compare the phenomenon that chemyon (face) not only affects the consumption behavior of Asia and the West universally (pan-culturally), but also distinctively (culture-specifically). That is, the purpose of this study is to describe that chemyon (face) is not only a culture-specific phenomenon but also a universal phenomenon in the consumption behavior of Asian and Western consumers, even though the extent that chemyon (face) impacts consumption behavior is differentiated. This study aims to understand commonalities and differences between Asian and Western consumption behavior in terms of chemyon (face), and to suggest how to enhance marketing effectiveness in a global market based on understanding the consumption behavior of Asia and the West. Research design, data, and methodology - Using systematic literature review and meta-analysis, this study investigates consumption behavior of Asian and Western consumers from the perspective of chemyon (face). Systematic literature review was used to compare face (chemyon) consumption of Western consumers with that of Asian consumers. To verify systematic literature review, meta-analysis was also accomplished. Results - First, the influence of face (chemyon) on consumption behavior is observed in Western consumers as well as Asian consumers. Second, Asian consumers are more influenced by face (chemyon) than Western consumers. Conclusions - Overall, chemyon (face) can affect the consumption behavior of Asians as well as the consumption behavior of Westerners.