• Journal of Korea Multimedia Society
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• v.19 no.6
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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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• v.21 no.2E
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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.

• Journal of Korea Multimedia Society
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• v.21 no.8
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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.

• Korean Journal of Child Studies
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• v.23 no.2
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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'.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.105-117
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• 2021

This study examined the factors that influence the emotional expression in comments on the hot news about the 'Restaurant Collapse in Linfen City, Shanxi Province' published in Sina Weibo.. As a result of the study, first, there were differences in emotional expression according to gender. Women expressed stronger anger, disappointment, sadness, and condemnation than men. Second, the intensity of emotional expression of users in the eastern region was significantly higher than that of users in the central and western region. Third, the greater the number of Weibo, the total number of blogs where users participated in comments and posted emotional expressions, the stronger the emotional expression was. Fourth, unauthenticated users showed stronger emotional expressions of disappointment and sadness than authenticated users. The results of this study present implications for the factors influencing emotional expression on hot news. This study is meaningful in that it can be compared with social networks such as Twitter and Facebook in the West by looking at the factors that influence emotional expression in the process of online public opinion formation in China, and also meaningful in that a big data analysis method was used in online news analysis.

• Journal of Oriental Neuropsychiatry
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• v.25 no.4
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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.

• Journal of the Ergonomics Society of Korea
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• v.31 no.3
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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.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.243-248
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• 2014

In this paper, we propose a method to recognize the facial expressions by selecting face elements and finding its status. The face elements are selected by using image area segmentation method and the facial expression is decided by using the normal distribution of the change rate of the face elements. In order to recognize the proper facial expression, we have built database of facial expressions of 90 people and propose a method to decide one of the four expressions (happy, anger, stress, and sad). The proposed method has been simulated and verified by face element detection rate and facial expressions recognition rate.

• Korean Journal of Computational Design and Engineering
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• v.19 no.4
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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.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.570-582
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• 2014

The purpose of this study was to investigate factors such as self-esteem, depression, anger expression and social support that affect the health promoting lifestyle in middle-aged women. Number of middle-aged women participated in the survey were 150. Data were collected by means of self reported questionnaires from 1. September to 30. November 2011 and analyzed by using descriptive statistics, t-test, ANOVA, Scheffe's test, Pearson's correlation coefficients and multiple regression with SPSS windows version 17.0. There were statistically significant differences in the health promoting lifestyle according to the frequency of physical activities, frequency of hobbies or social activities and menstruation state. There were significant positive correlations between health promoting lifestyle and self-esteem, anger-control and social support. Negative correlations were found between health promoting lifestyle and depression, anger-in and anger-out. Self-esteem, social support, frequency of physical activities and frequency of hobbies or social activities were predictors of a health promoting lifestyle. Nurses should focus on factors identified in this study when developing nursing interventions to improve a health promoting lifestyle for middle-aged women.