• 한국멀티미디어학회논문지
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• 제19권6호
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• pp.1014-1023
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• 2016

In this study, we presented a method for non-square Differential LBP operation that can well describe the micro pattern in the horizontal and vertical component. We proposed a way to represent a LBP operation with various direction components as well as the diagonal component. In order to verify the validity of the proposed operation, Differential LBP was investigated with respect to accuracy, sensitivity, and specificity for the classification of facial expression. In accuracy comparison proposed LBP operation obtains better results than Square LBP and LBP-CS operations. Also, Proposed Differential LBP gets better results than previous two methods in the sensitivity and specificity indicators 'Neutral', 'Happiness', 'Surprise', and 'Anger' and excellence Differential LBP was confirmed.

• The Journal of the Acoustical Society of Korea
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• 제21권2E호
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• pp.98-104
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• 2002

The present study describes a combination method to recognize the human affective states such as anger, happiness, sadness, or surprise. For this, we extracted emotional features from voice signals and facial expressions, and then trained them to recognize emotional states using hidden Markov model (HMM) and neural network (NN). For voices, we used prosodic parameters such as pitch signals, energy, and their derivatives, which were then trained by HMM for recognition. For facial expressions, on the other hands, we used feature parameters extracted from thermal and visible images, and these feature parameters were then trained by NN for recognition. The recognition rates for the combined parameters obtained from voice and facial expressions showed better performance than any of two isolated sets of parameters. The simulation results were also compared with human questionnaire results.

• 한국멀티미디어학회논문지
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• 제21권8호
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• pp.917-924
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• 2018

Recently, researches using LBP and SVM have been performed as one of the image - based methods for facial emotion recognition. LBP, introduced by Ojala et al., is widely used in the field of image recognition due to its high discrimination of objects, robustness to illumination change, and simple operation. In addition, CS(Center-Symmetric)-LBP was used as a modified form of LBP, which is widely used for face recognition. In this paper, we propose a method to detect four facial expressions such as expressionless, happiness, surprise, and anger using deep neural network. The validity of the proposed method is verified using accuracy. Based on the existing LBP feature parameters, it was confirmed that the method using the deep neural network is superior to the method using the Adaboost and SVM classifier.

• 아동학회지
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• 제23권2호
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• pp.31-47
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• 2002

In this study, the perceptions and responses of 136 kindergarten children from middle SES families were recorded in one-to-one interviews about the cause, reasons for expression, and responses to negative emotions. Results showed that children perceived he causes of anger and sadness as 'interpersonal events' and they perceived he cause of fear to be 'fantasy/scary events'. The children tended not to express their negative emotions because they expected negative responses from their peers and mothers, but when they did, the expressed their negative emotions to their mothers rather than to peers. Children responded to the negative emotions of their peers with 'problem-solving focused strategies', but they responded to their mothers' negative emotions with passive strategies, such as 'emotion focused response' and 'avoidance'.

• 한국콘텐츠학회논문지
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• 제21권5호
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• pp.105-117
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• 2021

본 연구는 시나 웨이보(Sina Weibo)에 게재된 '산시성 린펀시 반점 붕괴 사건'이라는 인기뉴스(hot news)에 대한 댓글에 나타난 감정표현에 영향을 미치는 요인들을 살펴보았다. 연구결과, 첫째, 성별에 따라 감정표현에 차이가 나타났다. 여성은 남성보다 더 강한 분노, 실망, 슬픔, 비난 감정을 표현하였다. 둘째, 동부지역 이용자들의 감정표현 강도가 중부지역과 서부지역에 비하여 유의하게 높았다. 셋째, 이용자가 댓글에 참여하고 감정표현을 게시한 블로그의 총수량인 웨이보 수가 많을수록 감정표현이 더욱 강하게 나타났다. 넷째, 미인증 이용자는 인증된 이용자보다 실망, 슬픔의 감정표현이 더욱 강하였다. 본 연구는 중국의 온라인 여론형성 과정에서 감정표현의 영향 요인을 살펴봄으로써 서양의 트위터나 페이스북과 같은 소셜네트워크와 비교할 수 있다는 점에서 의의가 있으며, 온라인 뉴스분석에서 빅데이터 분석방법을 사용했다는 점에서도 의의가 있다.

• 동의신경정신과학회지
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• 제25권4호
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• pp.319-332
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• 2014

Objectives: This study was conducted to evaluate the clinical effects of group therapy for Panic disorder patients based on Mindfulness & Li-Gyeung-Byun-Qi therapy. Methods: The FFMQ, BDI, STAI, STAXI, Panic attack, Anticipatory anxiety and subjective improvement of three Panic disorder patients were compared pre- and post-treatment when given Mindfulness & Li-Gyeung-Byun-Qi therapy. Results: 1) After the patient in case 1 underwent 5 weeks of group therapy for Panic disorder, the Mindfulness meditation score was slightly improved, anxiety and depression were significantly decreased, and expression of anger was also improved. In addition, the Panic attack and Anticipatory anxiety became more stable in the objective evaluation, while 'Extreme improvement' was shown in the subjective evaluation. 2) After the patients in case 2 and 3 underwent 5 weeks of group therapy for Panic disorder, Mindfulness meditation scores were slightly improved, anxiety and depression were significantly decreased, and expression of anger was also improved. In addition, the Panic attack and Anticipatory anxiety became more stable in the objective evaluation, while 'Moderate improvements' were shown in the subjective evaluation. Conclusions: As per the results in these cases, it was shown that group therapy for Panic disorder utilizing Mindfulness & Li-Gyeung-Byun-Qi therapy was effective to maintain meditation and control the emotions of anxiety, depression, anger and so on. Therefore, it was considered that expansion of clinical utilization through the standardization of a group therapy program for Panic disorder is needed. Furthermore, it was also considered that a comparative study of the effects of previous cognitive programs for Panic disorder according to the objectified and standardized manual is needed in the future.

• 대한인간공학회지
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• 제31권3호
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• pp.427-435
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• 2012

The aim of this study is to investigate facial temperature changes induced by facial expression and emotional state in order to recognize a persons emotion using facial thermal images. Background: Facial thermal images have two advantages compared to visual images. Firstly, facial temperature measured by thermal camera does not depend on skin color, darkness, and lighting condition. Secondly, facial thermal images are changed not only by facial expression but also emotional state. To our knowledge, there is no study to concurrently investigate these two sources of facial temperature changes. Method: 231 students participated in the experiment. Four kinds of stimuli inducing anger, fear, boredom, and neutral were presented to participants and the facial temperatures were measured by an infrared camera. Each stimulus consisted of baseline and emotion period. Baseline period lasted during 1min and emotion period 1~3min. In the data analysis, the temperature differences between the baseline and emotion state were analyzed. Eyes, mouth, and glabella were selected for facial expression features, and forehead, nose, cheeks were selected for emotional state features. Results: The temperatures of eyes, mouth, glanella, forehead, and nose area were significantly decreased during the emotional experience and the changes were significantly different by the kind of emotion. The result of linear discriminant analysis for emotion recognition showed that the correct classification percentage in four emotions was 62.7% when using both facial expression features and emotional state features. The accuracy was slightly but significantly decreased at 56.7% when using only facial expression features, and the accuracy was 40.2% when using only emotional state features. Conclusion: Facial expression features are essential in emotion recognition, but emotion state features are also important to classify the emotion. Application: The results of this study can be applied to human-computer interaction system in the work places or the automobiles.

• 디지털융복합연구
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• 제12권12호
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• pp.243-248
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• 2014

본 논문에서는 사람 얼굴의 표정을 인식하기 위하여 판단 요소를 선정하고 판단 요소의 변화 상태를 파악하여 표정을 인식하는 방법을 제안한다. 판단 요소를 선정하기 위하여 이미지 영역 분할 방법을 사용하며, 판단 요소의 변화율을 이용하여 표정을 판단한다. 표정을 판단하기 위하여 90명의 표정을 데이터베이스화하여 비교하였고, 4개의 표정(웃음, 화남, 짜증, 슬픔)을 인식하는 방법을 제안한다. 제안한 방법은 시뮬레이션을 실시하여 판단 요소 검출 성공률과 표정 인식률을 통해 검증한다.

• 한국CDE학회논문집
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• 제19권4호
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• pp.443-454
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• 2014

In this paper, an intuitive emotional expression of the 3D avatar is presented. Using the motion selection control of 3D avatar, an easy-to-use communication which is more intuitive than emoticon is possible. 12 pieces different emotions of avatar are classified as positive emotions such as cheers, impressive, joy, welcoming, fun, pleasure and negative emotions of anger, jealousy, wrath, frustration, sadness, loneliness. The combination of lower body motion is used to represent additional emotions of amusing, joyous, surprise, enthusiasm, glad, excite, sulk, discomfort, irritation, embarrassment, anxiety, sorrow. In order to get the realistic human posture, BVH format of motion capture data are used and the synthesis of BVH file data are implemented by applying the proposed emotional expression rules of the 3D avatar.

• 한국콘텐츠학회논문지
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• 제14권10호
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• pp.570-582
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• 2014

본 연구는 자아존중감, 우울, 분노표현방식, 사회적 지지가 중년여성의 건강증진 생활양식에 어떠한 영향을 미치는지 파악하기 위해 실시되었다. 연구 대상자는 150명의 중년여성이었으며 자가보고식 설문지를 이용하여 2011년 9월 1일부터 11월 30일까지 자료를 수집하였다. 자료 분석은 SPSS win 17.0 프로그램으로 기술적 통계, t-test, ANOVA, Scheffe's test, Pearson's correlation coefficients, 다중회귀분석으로 하였다. 연구 결과 신체운동을 자주 하는 집단과 취미생활이나 사회활동을 많이 하는 집단에서, 그리고 월경상태가 불규칙한 집단에 비해 규칙적이거나 폐경인 집단에서 건강증진 생활양식 점수가 높게 나타났다. 자아존중감, 분노조절, 사회적 지지는 건강증진 생활양식과 유의한 순상관관계를 보였고, 우울, 분노억제, 분노표출은 건강증진 생활양식과 역상관관계가 있는 것으로 나타났다. 자아존중감과 사회적 지지, 신체운동 횟수, 취미나 사회활동 횟수 등이 건강증진 생활양식을 예측하는 유의한 변수로 나타났다. 이 연구 결과에서 나타난 주요 예측변수들을 고려하여 중년여성의 건강증진 생활양식의 향상을 위한 간호중재 프로그램 개발이 요구된다.