• 한국의류산업학회지
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• 제11권1호
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• pp.103-111
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• 2009

This study is to help make-up and coordination for image-making after analysis of facial color and shape of elderly women. The data was analyzed 55-75 years old 212 elderly women's face color and pictures by means of SPSS 12.0 statistics package. On the basis of the colorimetric data on face by Minolta CM2500D, this research considered the analysis of facial color, patternization of facial color and its analysis by age group; for the analysis of facial shape, this research patternized facial shape and analyzed its characteristic using both contour-based facial shape analysis and Kamata facial shape analysis. As for facial color, it was found that the lower age bracket has bright and reddish face, looking fine, while the higher age bracket has a conspicuously yellowish face, looking bad. The community of facial color is classified as 3 types and it was found out that the facial color of the subjects belonging to Type 3, whose L value is the largest, looked the brightest; the face of the subjects belonging to Type 2, whose a value is the largest, was much tinged with red, and the face of the subjects belonging to Type 1, whose b value is the largest were tinged with yellow. According to the analysis of facial shape, there appeared oval & long forms in the classification by contour, while there appeared a lot of downward-directed power and inner-directed power in the classification by Kamata, which is believed to reflect the phenomenon that their chin line becomes roundish and the facial length also tend to be longer due to aging.

• 한국의류학회지
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• 제28권11호
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• pp.1470-1481
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• 2004

The purpose of this study was to research on facial shape to suggest a quantified data for the domestic apparel and beauty industry. Conducted a measurement research of 278 female college students, We took the photographs of front view and lateral view of the subjects by digital camera and obtained the 69 measurements through the facial measurement program. 264 ,subjects' measurement data were analyzed by various statistical methods such as descriptive analysis, factor analysis and cluster analysis. Using the 69 measurement items,4 factors were selected as key factors for the factor analysis of facial shape, the factors are: \circled1 Front face height \circled2 Side face radial length \circled3 Front face breadth \circled4 Ear height and Gnathion radial length. We categorized the facial shape into four types by cluster analysis. Type 4 is the most common facial shape in female college students: \circled1 Type 1: Round face \circled2 Type 2: Oval face \circled3 Type 3: Square face \circled4 Type 4: Heart shaped face According to the facial shape analysis, facial shape of female college students are consisting of Heart shaped face(34.8%), Round face(29.2%), Square face(23.5%), oval face(12.5%).

• Journal of Acupuncture Research
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• 제34권3호
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• pp.23-38
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• 2017

Objectives : The purpose of this study was to evaluate the clinical prognostic factors affecting facial palsy in 98 idiopathic facial palsy patients who were hospitalized and treated in 2015, using retrospective statistical analysis. Methods : We investigated patients with idiopathic facial nerve palsy, admitted to a Korean medical hospital in 2015, and examined patients' variables and therapeutic variables. For analysis of clinical data, an independent sample t-test, analysis of variance (ANOVA), and simple regression analysis were performed using IBM SPSS version 24.0. Results : 1. The initial degree of facial palsy showed statistical significance with age. The older the age, the more severe the initial palsy. 2. Following treatment degree of facial palsy was statistically significant with age, hypertension, and fasting blood sugar (FBS). The higher the value, the slower the recovery from facial palsy. There was a statistical significance with the number of treatments in a Korean medical hospital. The more frequent the treatment, the faster the facial palsy recovery. 3. Degree of facial palsy after 12 months was statistically significant with age, hypertension, diabetes, FBS, and the initial severity of facial palsy. The higher the value, the slower the facial palsy recovery. 4. Sex, left or right sided palsy, alcohol consumption, smoking, history of facial palsy, season of onset, total number of treatments and bio chemistry (BC), complete blood cell count (CBC), urinalysis (UA) factors had no statistical significance with prognosis of facial palsy. Conclusion : Age, season of onset, hypertension, diabetes, FBS, initial severity of facial palsy, and the number of treatments at a Korean medical hospital showed statistical significance. The number of treatments at the Korean medical hospital positively correlated with facial palsy prognosis, and the others variables showed a negative correlation with facial palsy prognosis.

• Asian Journal for Public Opinion Research
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• 제8권3호
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• pp.180-196
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• 2020

This paper considers Japanese political interviews to integrate conversation and facial expression analysis. The behaviors of political leaders will be disclosed by analyzing questions and responses by using the turn-taking system in conversation analysis. Additionally, audiences who cannot understand verbal expressions alone will understand the psychology of political leaders by analyzing their facial expressions. Integral analyses promote understanding of the types of facial and verbal expressions of politicians and their effect on public opinion. Politicians have unique techniques to convince people. If people do not know these techniques and ways of various expressions, they will become confused, and politics may fall into populism as a result. To avoid this, a complete understanding of verbal and non-verbal behaviors is needed. This paper presents two analyses. The first analysis is a qualitative analysis that deals with Prime Minister Shinzō Abe and shows that differences between words and happy facial expressions occur. That result indicates that Abe expresses disgusted facial expressions when faced with the same question from an interviewer. The second is a quantitative multiple regression analysis where the dependent variables are six facial expressions: happy, sad, angry, surprised, scared, and disgusted. The independent variable is when politicians have a threat to face. Political interviews that directly inform audiences are used as a tool by politicians. Those interviews play an important role in modelling public opinion. The audience watches political interviews, and these mold support to the party. Watching political interviews contributes to the decision to support the political party when they vote in a coming election.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 1부
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• pp.667-674
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• 2007

Facial expressions provide significant clues about one's emotional state; however, it always has been a great challenge for machine to recognize facial expressions effectively and reliably. In this paper, we report a method of feature-based adaptive motion energy analysis for recognizing facial expression. Our method optimizes the information gain heuristics of ID3 tree and introduces new approaches on (1) facial feature representation, (2) facial feature extraction, and (3) facial feature classification. We use minimal reasonable facial features, suggested by the information gain heuristics of ID3 tree, to represent the geometric face model. For the feature extraction, our method proceeds as follows. Features are first detected and then carefully "selected." Feature "selection" is finding the features with high variability for differentiating features with high variability from the ones with low variability, to effectively estimate the feature's motion pattern. For each facial feature, motion analysis is performed adaptively. That is, each facial feature's motion pattern (from the neutral face to the expressed face) is estimated based on its variability. After the feature extraction is done, the facial expression is classified using the ID3 tree (which is built from the 1728 possible facial expressions) and the test images from the JAFFE database. The proposed method excels and overcomes the problems aroused by previous methods. First of all, it is simple but effective. Our method effectively and reliably estimates the expressive facial features by differentiating features with high variability from the ones with low variability. Second, it is fast by avoiding complicated or time-consuming computations. Rather, it exploits few selected expressive features' motion energy values (acquired from intensity-based threshold). Lastly, our method gives reliable recognition rates with overall recognition rate of 77%. The effectiveness of the proposed method will be demonstrated from the experimental results.

• Archives of Plastic Surgery
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• 제33권2호
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• pp.168-174
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• 2006

For over two thousand years, many artists and scientists have tried to understand or quantify the form of the perfect, ideal, or the most beautiful face both in art and in vivo(life). However, this mathematical relationship has been consistently and repeatedly reported to be present in beautiful things. This particular relationship is referred to as the golden ratio. It is a mathematical ratio of 1.618 : 1 that seems to appear recurrently in beautiful things in nature as well as in other things that are seen as beautiful. Dr. Marquardt made the facial golden mask that contains and includes all of the 1-dimensional and 2-dimensional geometric golden element formed from the golden ratio. The purpose of this study is to evaluate the usefulness of the golden facial mask. In our cases(n=40), the authors applied the facial golden mask to the preoperative and postoperative photographs, and scored each photograph. Compared with the average scores of the facial mask applied photographs and none applied photographs using non-parametric test, statistical significance was not checked (p > 0.05). It means that the facial golden mask can be used for facial analysis. The facial golden mask is easy to apply, cheap and relatively objective. So, the authors introduce the one of useful facial analyses.

• 반도체디스플레이기술학회지
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• 제16권4호
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• pp.79-85
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• 2017

Understanding of human emotion has a high importance in interaction between human and machine communications systems. The most expressive and valuable way to extract and recognize the human's emotion is by facial expression analysis. This paper presents and implements an automatic extraction and recognition scheme of facial expression and emotion through still image. This method has three main steps to recognize the facial emotion: (1) Detection of facial areas with skin-color method and feature maps, (2) Creation of the Bezier curve on eyemap and mouthmap, and (3) Classification and distinguish the emotion of characteristic with Hausdorff distance. To estimate the performance of the implemented system, we evaluate a success-ratio with emotional face image database, which is commonly used in the field of facial analysis. The experimental result shows average 76.1% of success to classify and distinguish the facial expression and emotion.

• 산업융합연구
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• 제13권2호
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• pp.45-54
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• 2015

This Study aims to analyze the factors for the success of commercialization of the facial extraction and recognition image security information system of the domestic companies in Korea. As the results of the analysis, the internal factors for the success of commercialization of the facial extraction and recognition image security information system of the company were found to include (1) Holding of technology for close range facial recognition, (2) Holding of several facial recognition related patents, (3) Preference for the facial recognition security system over the fingerprint recognition and (4) strong volition of the CEO of the corresponding company. On the other hand, the external environmental factors for the success were found to include (1) Extensiveness of the market, (2) Rapid growth of the global facial recognition market, (3) Increased demand for the image security system, (4) Competition in securing of the engine for facial extraction and recognition and (5) Selection by the government as one of the 100 major strategic products.

• 한국정보과학회논문지:소프트웨어및응용
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• 제27권8호
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• pp.827-833
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• 2000

본 논문에서는 인간의 중요한 감정표현 수단인 얼굴표정을 분석하는 방법을 제시하였다. 제안된 방법에서는 기준얼굴과 그의 혼합 비율의 관점에서 얼굴표정을 분석한다. 기준얼굴은 인간의 대표적인 얼굴표정인 놀람, 두려움, 분노, 혐오, 행복, 슬픔, 그리고 무표정으로 설정하였다. 얼굴 모델의 생성을 위해 일반 얼굴 모델이 얼굴영상으로 정합하는 방법을 사용하였다. 기준얼굴의 혼합 비율을 구하기 위해 유전자 알고리즘과 Simulated Annealing 방법을 사용하였고 탐색된 얼굴표정 정보를 이용한 얼굴표정 생성 실험을 통해 제안된 방법의 유용성을 입증하였다.

• 대한두개안면성형외과학회지
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• 제13권1호
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• pp.36-40
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• 2012

Purpose: Statistical analysis of facial bone fractures has been performed in various papers. However, reports on risk factors for facial bone fractures are rare. In order to prevent facial bone fractures, it is important to determine the risk factors for their occurrence. This study seeks to perform a statistical analysis on and identify the risk factors associated with facial bone fractures. Methods: A retrospective study was performed to assess facial bone fractures in patients presenting from October 2009 to January 2011 through a chart review. The data collected included age, gender, etiology, and alcohol consumption. Data was analyzed using multinomial logistic regression analysis. The significance level was set at p<0.05 and SAS ver. 9.2 was used. Results: A total of 489 patients were analyzed. The patients' age ranged from 2 to 85 years (mean age, $31.8{\pm}15.4$ years). The ratio of men to women was 5.0:1. The predominant group was age below 19 years old (30.9%). The main causes of facial bone fractures were assaults (37.8%), falls (27.2%), and sport accidents (19.5%). On multinomial logistic regression analysis, age, especially in the teen group was associated with assaults (p<0.05) resulting in facial bone fractures. Alcohol consumption was significantly associated with assaults and falls (p<0.05) leading to facial bone fractures. Conclusion: Facial bone fracture is a challenging problem, because of its high incidence and financial cost. The findings of this study indicate that more effective policies aimed at reducing alcohol intake and teenage violence are needed.