• Human Ecology Research
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• v.52 no.1
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• pp.1-10
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• 2014

The purpose of this study was to analyse the principles and methods of Taegyo-Singi with regard to emotion and to review basic informations on Taegyo programs for promoting prenatal development. Taegyo-Singi was analyzed as follows. First, the contents of Taegyo-Singi were classified into principles and methods of Taegyo. Second, the domains of emotion were categorized into emotional perception, emotional expression, emotional understanding, and emotional regulation based on the classification of Mayer and Salovey, and Moon. Third, the contents of Taegyo-Singi were classified into the four domains of emotion. Finally, the reliability and validity of the classification were obtained through inter-rater agreement and analysis of content validity. The results indicated that first, the principles of Taegyo presuppose parental influence on temperament formation, and that the emotional states of the mother in the prenatal and prepregnancy period is the most influential variable in a child's temperament formation. Second, the methods of Taegyo presuppose that the human mind interacts with their behavior. Therefore, through emotional support of family members, 'jon-sim (the serene mind)' and 'chung-sim (the mind from rectitude)' are the key methods of Taegyo. This means that the Korean tradition of Taegyo focused on the emotional domain of development, especially emotional regulation. This coincides with the emotion-focused temperament theory that individual differences in temperament reflect individual differences in emotion.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.130-133
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• 2004

인간의 감정을 정의하거나 분류하는 것은 매우 어려운 일이다. 이러한 애매모호한 인간의 감정은 어느 한 감정만 나타나는 것이 아니고 다양한 감정의 복합으로, 눈에 띄는 강정이 드러나는 것이다. 인간의 애매모호한 감정 상태와 유사한 감성을 표현하는 알고리즘으로 dynamic emotion Space를 이용한 감성 표현 알고리즘을 제안한다. 기존의 감성 표현 아바타들이 키리 설정된 몇개의 감정만을 데이터 베이스에서 불러와 표현하는 반면에, 본 논문에서 제안하는 감성 표현 시스템은 동적으로 변화하는 감성 공간을 이용하여 감성을 표현함으로써 무수히 다양한 표정을 표현할 수 있다. 실제로 인간의 복합적이고 다양한 표정을 표현할 수 있는지를 알아보기 위해 실제 구현 및 실험을 수행하고, dynamic emotion space를 이용한 감성 표현 시스템의 성능을 입증한다.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1383-1392
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• 2014

In this paper, we proposed a method to automatically determine the optimal radius through multi-scale LBP operation generalizing the size of radius variation and boosting learning in facial emotion recognition. When we looked at the distribution of features vectors, the most common was $LBP_{8.1}$ of 31% and sum of $LBP_{8.1}$ and $LBP_{8.2}$ was 57.5%, $LBP_{8.3}$, $LBP_{8.4}$, and $LBP_{8.5}$ were respectively 18.5%, 12.0%, and 12.0%. It was found that the patterns of relatively greater radius express characteristics of face well. In case of normal and anger, $LBP_{8.1}$ and $LBP_{8.2}$ were mainly distributed. The distribution of $LBP_{8.3}$ is greater than or equal to the that of $LBP_{8.1}$ in laugh and surprise. It was found that the radius greater than 1 or 2 was useful for a specific emotion recognition. The facial expression recognition rate of proposed multi-scale LBP method was 97.5%. This showed the superiority of proposed method and it was confirmed through various experiments.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.8-17
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• 2019

The main purpose of this study isto explore the potential of affective computing (AC) platforms in education through two phases ofresearch: Phase I - platform analysis and Phase II - classification of academic emotions. In Phase I, the results indicate that the existing affective analysis platforms can be largely classified into four types according to the emotion detecting methods: (a) facial expression-based platforms, (b) biometric-based platforms, (c) text/verbal tone-based platforms, and (c) mixed methods platforms. In Phase II, we conducted an in-depth analysis of the emotional experience that a learner encounters in online video-based learning in order to establish the basis for a new classification system of online learner's emotions. Overall, positive emotions were shown more frequently and longer than negative emotions. We categorized positive emotions into three groups based on the facial expression data: (a) confidence; (b) excitement, enjoyment, and pleasure; and (c) aspiration, enthusiasm, and expectation. The same method was used to categorize negative emotions into four groups: (a) fear and anxiety, (b) embarrassment and shame, (c) frustration and alienation, and (d) boredom. Drawn from the results, we proposed a new classification scheme that can be used to measure and analyze how learners in online learning environments experience various positive and negative emotions with the indicators of facial expressions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.186-191
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• 2015

Hand gesture is the most common tool used to interact with and control various electronic devices. In this paper, we propose a novel hand gesture recognition method using fuzzy logic based classification with a new type of sensor array. In some cases, feature patterns of hand gesture signals cannot be uniquely distinguished and recognized when people perform the same gesture in different ways. Moreover, differences in the hand shape and skeletal articulation of the arm influence to the process. Manifold features were extracted, and efficient features, which make gestures distinguishable, were selected. However, there exist similar feature patterns across different hand gestures, and fuzzy logic is applied to classify them. Fuzzy rules are defined based on the many feature patterns of the input signal. An adaptive neural fuzzy inference system was used to generate fuzzy rules automatically for classifying hand gestures using low number of feature patterns as input. In addition, emotion expression was conducted after the hand gesture recognition for resultant human-robot interaction. Our proposed method was tested with many hand gesture datasets and validated with different evaluation metrics. Experimental results show that our method detects more hand gestures as compared to the other existing methods with robust hand gesture recognition and corresponding emotion expressions, in real time.

• Journal of the Ergonomics Society of Korea
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• v.33 no.5
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• pp.323-335
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• 2014

Objective: The aim of this study is to identify the relationship between personality and psychological responses induced by emotional stimuli (happiness, sadness, anger, boring and stress) for children. Background: Many researches are interested in assertion that there is close correlation between personality and emotion. The relationship between personality and emotion needs to be studied in view of the extended integration, not in view of respective property, because personality is deeply ingrained, and the relatively enduring patterns of thought, feeling and behavior and emotion can take advantage of individual differences in sensitivities to situational cues and predispositions to emotional state. In particular, studies on the personality and emotion for children are necessary in that childhood is an important period for formation of their personality and emotion expression and regulation. Method: Prior to the experiment, we made parents of 94 children rate personalities of their children, based on Korean Personality Inventory for Children (K-PIC). Results of 64 children without missing answers to all questions were analyzed. 64 children were exposed to five emotional stimuli and were asked to report the classification and intensity of their experienced emotion. Results: Children were classified into two groups of the lower 25% and higher 25% scores in twenty sub-scales of K-PIC, and psychological responses to five emotional stimuli between two groups were compared. Accuracy of emotion experienced by emotional stimuli showed a significant difference between the two groups, the lower and higher scores in Hyperactivity and Adjustment. Also, there was a significant difference in the intensity of experienced emotions between the two groups in Intellectual Screening and Psychosis. Conclusion: Our result has shown that hyperactivity, adjustment, intellectual screening and psychosis influence the accuracy and intensity of emotional responses. Application: This study can offer a guideline to overcome methodological limitation of emotion studies for children and help researcher basically understand and recognize human emotion in HCI.

• Korean Institute of Interior Design Journal
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• v.17 no.1
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• pp.170-177
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• 2008

If we consider the cubism, which newly attempted the avant-garde movement in the mid-19th century, was an experimental movement to feel the space through the human action and observation from various viewpoints at the fixed three-dimensional world, then the futurism was an innovative movement that obtained an ion from continual motions. However, the study about meaning and emotion that correspond with the dis-structuralization era could not have been continuing. Therefore, the goal of this study is to construct an emotional theory and grope a possibility of the way to do through some theoretical investigations and experimental analysis about body movement and emotional expression. For the study method, experiment and analysis have been proceeded based on Miyauji study(1992) which was based on P. Thiel theory that is about direct recognition and empirical study for identical existence or experimentation. As a result of the study, it reached several conclusions. The first, body movement as an emotion that makes meaning is related to the space. The second is that the space is related to the background as an object of body. The last is that body as a creature which becomes the one with spirit in the space makes meaning. We look forward to a possibility of emotional study through the body movement.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.834-839
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• 2009

It is a key element that the problem of emotional feature extraction based on facial image to recognize a human emotion status. In this paper, we propose an Advanced AAM that is improved version of proposed Facial Expression Recognition Systems based on Bayesian Network by using FACS and AAM. This is a study about the most efficient method of optimal facial feature area for human emotion recognition about random user based on generalized HCI system environments. In order to perform such processes, we use a Statistical Shape Analysis at the normalized input image by using Advanced AAM and FACS as a facial expression and emotion status analysis program. And we study about the automatical emotional feature extraction about random user.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.155-161
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• 2024

In this paper, we propose a new model by adding landmark information as a feature vector to the existing CNN-based facial emotion classification model. Facial emotion classification research using CNN-based models is being studied in various ways, but the recognition rate is very low. In order to improve the CNN-based models, we propose algorithms that improves facial expression classification accuracy by combining the CNN model with a landmark-based fully connected network obtained by ASM. By including landmarks in the CNN model, the recognition rate was improved by several percent, and experiments confirmed that further improved results could be obtained by adding FACS-based action units to the landmarks.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.203-212
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• 2022

The purpose of this study is to investigate the nature of the experience of Emotion Focused Psychology Coaching, and what kind of changes happened for the participants through the experience. For this, in-depth interviews were conducted with four participants who had experienced five sessions of Emotion Focused Psychology Coaching. The interviews were analyzed using the phenomenological analysis method of Colaizzi. Emotion Focused Psychology Coaching is a new coaching psychology model that combines Greenberg's Emotion-Focused Therapy (EFT) and the ICF Core Competencies. The findings show that prior to the experience of Emotion Focused Psychology Coaching, the participants had avoided or suppressed their emotions, which in turn prevented them from exploring effective interpersonal relationships or alternatives in their actions. On the other hand, after they experienced Emotion Focused Psychology Coaching, their perception of emotions, emotion regulation, emotional expression, empathy for the other, etc. were developed in adaptive ways and the participants could present effective alternatives.