• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.4
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• pp.54-62
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• 2011

Emotional reaction should be different from the purpose of the robot system. The method for emotional reaction is also different from the specification of the robot system. Therefore, emotional behavior decision model, which is applied to social robots regardless of specifications and purposes, is necessary. This paper introduces a universal emotional behavior decision model designed for applying to various social robots that have different specifications and purposes. Multiple emotions, a set of probability value of every emotion, are calculated independently and expressed according to the purpose of the robot system. Then, behavior, for emotional reaction according to the calculated multiple emotions, is decided regarding the specification of the robot system. The decided behavior is a combination of unit behaviors that indicates the smallest expressible behaviors in each expression parts. It is possible to express various undefined behaviors by generating unit behavior combinations according to multiple emotions. The universal emotional behavior decision model is applied to three kinds of social robot systems that have different specifications and purposes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.239-246
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• 2021

In the field of computer graphics and HCI, there are many studies on systems that create characters and interact naturally. Such studies have focused on the user's response to the user's behavior, and the study of the character's behavior to elicit positive emotions from the user remains a difficult problem. In this paper, we develop a prototype of an interaction system to elicit positive emotions from users according to the movement of virtual characters using artificial intelligence technology. The proposed system is divided into face recognition and motion generation of a virtual character. A depth camera is used for face recognition, and the recognized data is transferred to motion generation. We use imitation learning as a learning model. In motion generation, random actions are performed according to the first user's facial expression data, and actions that the user can elicit positive emotions are learned through continuous imitation learning.

• Journal of the Korean Society of Costume
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• v.23
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• pp.53-65
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• 1994

The images signifying flight in modern costumes are not made of one characteristic but the combination of complex meanings. Among the distinctive features some of them are as follows. First, the flying styles found in the costumes showed the birds as agents which sent human spirit to the celestial body. By simplifying the images of the wings connecting the present age with the heavenly body, the transforming emotions towards rhythm, direction, and organic curves transcending the real objectively constitutes a new space for expression. Second, colors appeal directly to man's emotions and incites emotional responses. The flying was shown in lines and colors. By using horizontal , vertical, oblique, and spiral lines and contrasted and paralleled colors, man's desire to fly dwells in newly colored space by reflecting speculative emotion through uniting surface. Third, the flying except for the costumes can be found in the advertisement through model's pose and camera technique, the flying itself is described through model's pose, the materials of the costumes, details, and sustaining stuffs. This symbolizes man's wish towards the unknown world vividly and dynamically. As discussed above the spirit of flying was, when expressed distinctively , in accordance with the varying cultural traits and transitions. The shape made by the vitality of symbolizing flying birds and animals along with the flying in the natural aspects such as wind and cloud were reappeared, simplified and symbolized , in modern costumes as consituting a new modeling space.

• Korean Journal of Child Studies
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• v.36 no.2
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• pp.145-166
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• 2015

The main purpose of this study was to examine the direct and indirect effects of maternal meta-emotion on preschoolers' emotional intelligence through mothers' emotion socialization. A total of 252 preschool-aged children and their mothers residing in the Seoul Metropolitan and Gyeonggi-do areas participated in this study. The mothers completed questionnaires regarding their meta-emotion, emotion socialization and preschoolers' emotional intelligence. The results of the study indicated that maternal meta-emotion did not have a direct effect on preschoolers' emotional intelligence. However, maternal meta-emotion did indeed have an indirect effect on preschoolers' emotional intelligence through emotion socialization styles. That is, mothers who had desirable beliefs about emotions provided supportive reactions to children's negative emotion expression and showed positive emotions more frequently in the family. In addition, the preschoolers of mothers who showed positive emotion socialization styles were reported to be more emotionally intelligent. The findings of this study suggest that maternal meta-emotion and emotion socialization are important in predicting preschoolers' emotional intelligence.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.83-94
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• 2011

Main researching issue in affective computing is to give a machine the ability to recognize the emotion of a person and to react it properly. Efforts in that direction have mainly focused on facial and oral cues to get emotions. Postures have been recently considered as well. This paper aims to discriminate emotions posture by identifying and measuring the saliency of posture features that play a role in affective expression. To do so, affective postures from human subjects are first collected using a motion capture system, then emotional features in posture are described with spatial ones. Through standard statistical techniques, we verified that there is a statistically significant correlation between the emotion intended by the acting subjects, and the emotion perceived by the observers. Discriminant Analysis are used to build affective posture predictive models and to measure the saliency of the proposed set of posture features in discriminating between 6 basic emotional states. The evaluation of proposed features and models are performed using a correlation between actor-observer's postures set. Quantitative experimental results show that proposed set of features discriminates well between emotions, and also that built predictive models perform well.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.565-577
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• 2024

This discussion looked at how emotional adjectives are connected in the format [[emotional adjective + '-ko(and)'] + emotional adjective]. As a result, it was confirmed that there are quite a few cases in which two or more emotional adjectives are used to express emotions in Korean. This can help Korean learners understand and express the individual lexical meanings of emotional adjectives more clearly by identifying emotional adjectives that are used together with the corresponding configuration. It was believed that it could help Korean language learners express complex emotions or create rich emotional expressions when expressing their emotions in Korean. It is hoped that the examples and frequency of [[emotional adjective+'-ko(and)'+emotional adjective] shown in this discussion will be of some help in teaching and learning Korean emotional vocabulary.

• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.139-146
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• 2014

This paper proposes an efficient method for automatically distinguishing various facial expressions. To recognize the emotions from facial expressions, the facial images are obtained by digital cameras, and a number of feature points were extracted. The extracted feature points are then transformed to 49-dimensional feature vectors which are robust to scale and translational variations, and the facial emotions are recognized by statistical pattern classifiers such Naive Bayes, MLP (multi-layer perceptron), and SVM (support vector machine). Based on the experimental results with 5-fold cross validation, SVM was the best among the classifiers, whose performance was obtained by 50.8% for 6 emotion classification, and 78.0% for 3 emotions.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.55-70
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• 2009

Vision-based Human computer interaction is an emerging field of science and industry to provide natural way to communicate with human and computer. In that sense, inferring the emotional state of the person based on the facial expression recognition is an important issue. In this paper, we present a novel approach to recognize facial expression from a sequence of input images using emotional specific HMM (Hidden Markov Model) and facial motion tracking based on optical flow. Conventionally, in the HMM which consists of basic emotional states, it is considered natural that transitions between emotions are imposed to pass through neutral state. However, in this work we propose an enhanced transition framework model which consists of transitions between each emotional state without passing through neutral state in addition to a traditional transition model. For the localization of facial features from video sequence we exploit template matching and optical flow. The facial feature displacements traced by the optical flow are used for input parameters to HMM for facial expression recognition. From the experiment, we can prove that the proposed framework can effectively recognize the facial expression in real time.

• Journal of the Korean Society of Costume
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• v.60 no.8
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• pp.1-14
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• 2010

This study is a discussion of the expressive characteristics of contemporary fashion design with floral images. It aims to help understand the overall trends of contemporary fashion design and textile motif design and expand the potential expression fields of originative design to natural objects such as flowers. Methodologically the study analyzed 976 pieces of data gathered from Haute Couture and Pr$\hat{e}$t-$\grave{a}$-Porter collections of 2005S/S-2009F/W, according to their types of expression. The study results show a share of 42.7% for plane type expressions by printing or weaving and a share of 51.5% for relief type expressions, compared with 5.7% for solid type expressions. However, those expressions represented elegant femininity with emphasis on formative beauty and were applied to fashion accessories or hair adornments. The expressive characteristics found from the analysis were represented by natural images, feminine elegance, and decorative aesthetics of handicrafts. Flowers in the contemporary fashion purify the internal emotions of humankind stand for personality and beauty in many different ways of expression and serve as a means of expressing more artistic values breaking out of stereotype.