• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.29 no.3
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• pp.63-72
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• 2023

Background: This study investigated the effects of face-to-face and non-face-to-face McKenzie exercises and elastic band strengthening exercises on falls and fitness in older adults. Methods: A total of 44 subjects were divided into a face-to-face group (FG; n=22) and a non-face-to-face group (NFG; n=22) who met older adults. Both groups used McKenzie exercises and strength training with elastic bands The fall efficacy scale (K-FES) and glycosylated hemoglobin (HbA1c) Pro were used to compare the senior fitness test (SFT). Results: No significant differences were detected between the two groups before the intervention; however, a significant difference was noted in the K-FES scores after the intervention. The change in HbA1c after the intervention was not statistically significant in the FG or the NFG, and no significant difference was detected between the two groups. The change in lower limb muscle strength in the elderly physical fitness test showed no significant difference between the two groups before or after the intervention. The change in upper limb flexibility after the intervention was not significantly different in the FG or NFG, indicating no significant difference between the two groups. The change in the 3-meter round-trip test after the intervention was significantly different in both the FG and NFG groups, but the difference between the groups was not statistically significant. The change in the grip strength test of the dominant hand showed no significant difference after the intervention in the FG or the NFG, and the difference between the FG and NFG groups was not statistically significant. The dominant foot external standing after the intervention was significantly improved in the FG, but no significant difference was detected in the NFG, and the difference between the two groups was not statistically significant. Conclusion: The study findings revealed that FG and NFG McKenzie exercises and elastic band strengthen exercises were equally effective at preventing falls and improving fitness in older adults.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.402-410
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• 2017

For many years, researchers in face description area have been representing and recognizing faces based on different methods that include subspace discriminant analysis, statistical learning and non-statistics based approach etc. But still automatic face recognition remains an interesting but challenging problem. This paper presents a novel and efficient face image representation method based on Optimized Local Ternary Pattern (OLTP) texture features. The face image is divided into several regions from which the OLTP texture feature distributions are extracted and concatenated into a feature vector that can act as face descriptor. The recognition is performed using nearest neighbor classification method with Chi-square distance as a similarity measure. Extensive experimental results on Yale B, ORL and AR face databases show that OLTP consistently performs much better than other well recognized texture models for face recognition.

• Science of Emotion and Sensibility
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• v.4 no.1
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• pp.7-14
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• 2001

Based on the past research works on the relationship between face type and personality, personality and purchasing behavior, personality and preference for color, face type and preference for color, we assumed that there could be certain differences in preferred color tone in purchasing automobile according to face type. Objective of this paper is to analyze what differences there are preferred color tones of purchasing automobile by face type. The questionnaires on preferred color tone of automobile were investigated, and the tone of color were classified into light, dark, brilliant, plain tones, and the differences of preferred color tone of purchasing automobile were analyzed by the face types. The result showed the facts that compared with the other types, the rectangular face type preferred the light tone of color, whereas the other face types little showed a distinctive inclination for a particular color tone. Results of this research could be utilized for automobile sales policy for materials of research into color tones, provided some problems are fixed and the concrete researches into relationship between face type and personality, purchasing behavior, preference for color are carried out.

• Korean Management Science Review
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• v.33 no.3
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• pp.65-87
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• 2016

Being the FinTech technologies rapidly developed, the non face-to-face private loan market is also growing dramatically. While the real-world interests in this market are keen, the empirical studies on the issue are few compared to its prospective impact on credit loan market. This paper suggests a credit scoring model for the non face-to-face private loan employing the ratings approach (the absolute measurement method) of AHP. Analyzing a sample of data consisting of 460,000 transaction records over an 8-year period in the United States, we develop a scoring model for the non face-to-face private loan screening, and validate the model for the practical usage. Conducting sensitivity analysis, we suggest customized cut-off points for the loan execution to suit each individual loan institution's need.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.594-600
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• 2003

In this paper, we propose a detection method for facial features in color images with various backgrounds and face poses. To begin with, the proposed method extracts face candidacy region from images with various backgrounds, which have skin-tone color and complex objects, via the color and edge information of face. And then, by using the elliptical shape property of face, we correct a rotation, scale, and tilt of face region caused by various poses of head. Finally, we verify the face using features of face and detect facial features. In our experimental results, it is shown that accuracy of detection is high and the proposed method can be used in pose-invariant face recognition system effectively

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1692-1699
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• 2004

Many researchers have developed various techniques for detection of human faces in ordinary still images. Face detection is the first imperative step of human face recognition systems. The two main problems of human face detection are how to cutoff the running time and how to reduce the number of false positives. In this paper, we present frontal and near-frontal face detection algorithm in still gray images using a thick edge image and neural network. We have devised a new filter that gets the thick edge image. Our overall scheme for face detection consists of two main phases. In the first phase we describe how to create the thick edge image using the filter and search for face candidates using a whole face detector. It is very helpful in removing plenty of windows with non-faces. The second phase verifies for detecting human faces using component-based eye detectors and the whole face detector. The experimental results show that our algorithm can reduce the running time and the number of false positives.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.499-505
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• 2003

This paper proposes methods to extract face elements and facial characteristics points for face recognition. We select a candidate region of the face elements with geometrical information between them inside the extracted face region with skin color and extract them using their inherent features. The facial characteristics to be applied to face recognition is expressed with geometrical relation such as distance and angle between the extracted face elements. Experiment results shows good performance to extract of face elements.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1013-1014
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• 2008

In this paper, we propose a new method of generating 3D face by using single frontal face image and 3D generic face model. By using active appearance model (AAM), the control points among facial feature points were localized in the 2D input face image. Then, the transform parameters of 3D generic face model were found to minimize the error between the 2D control points and the corresponding 2D points projected from 3D facial model. Finally, by using the obtained model parameters, 3D face was generated. We applied this 3D face to 3D game framework and found that the proposed method could make a realistic 3D face of game user.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.575-578
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• 1999

The principal features of a face are as follows : skin-tone, symmetry, and requisites such as shape of ellipse, eyes, nose, mouth. Also, faces have different size, various shape and position. In case of application of face recognition and detection without preprocessing, efficiency of the performance is decreased. In addition, face itself, complex background, image quality, etc. are included. Therefore, previous face recognition methods are implemented on the base of specific constraints of the face image. In this paper, we propose the efficient and automatic face detection algorithm for minimizing influence such as complex background, image quality, etc. This face detection technique consists of skin-tone, candidate face region and face region extractions.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.113-116
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• 2000

Human face recognition and 3D human face reconstruction has been studied in this paper. To find the facial feature points, find edge from input image and analysis the accumulated histogram of edge information. This paper use a Generic Face Model to display the 3D human face model which was implement with OpenGL and generated with 500 polygons. For reality of 3D human face model, we propose Group matching mapping method between facial feature points and the one of Generic Face Model. The personalized 3D human face model which resembles real human face can be generated automatically in less than 5 seconds on Pentium PC.