• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.29-40
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• 2012

A challenging research issue that has been one of growing importance to those working in human-computer interaction are to endow a machine with an emotional intelligence. Thus, emotion recognition technology plays an important role in the research area of human-computer interaction, and it allows a more natural and more human-like communication between human and computer. In this paper, we propose the multimodal emotion recognition system using face and speech to improve recognition performance. The distance measurement of the face-based emotion recognition is calculated by 2D-PCA of MCS-LBP image and nearest neighbor classifier, and also the likelihood measurement is obtained by Gaussian mixture model algorithm based on pitch and mel-frequency cepstral coefficient features in speech-based emotion recognition. The individual matching scores obtained from face and speech are combined using a weighted-summation operation, and the fused-score is utilized to classify the human emotion. Through experimental results, the proposed method exhibits improved recognition accuracy of about 11.25% to 19.75% when compared to the most uni-modal approach. From these results, we confirmed that the proposed approach achieved a significant performance improvement and the proposed method was very effective.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.256-261
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• 2007

Electroencephalographic(EEG) is used to record activities of human brain in the area of psychology for many years. As technology developed, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study Emotion Recognition method which uses one of EEG signals and Gestures in the existing research. In this paper, we use together EEG signals and Gestures for Emotion Recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both EEG signals and gestures gets high recognition rates better than using EEG signals or gestures. Both EEG signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on the reinforcement learning.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.14 no.2
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• pp.13-24
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• 2010

Background and purpose: Seven Emotions consist of Joy(喜), Anger(怒), Anxiety(憂), Thought(思), Sorrow(悲), Fear(恐), Fright(驚). If Seven Emotion is excessive, its extreme mental stimulation causes physical illness. There was no study of the Seven Emotion Disease in detail for now. Therefore the purpose of this study is to pigeonhole the Seven Emotion Disease. Methods: We extract the sentences about the Seven Emotion and related words in Donguibogam. We classify the sententences into Joy(喜), Anger(怒), Anxiety(憂), Thought(思), Sorrow(悲), Fear(恐), Fright(驚), Frustration, Mental Exhaustion, Character. We analysis pattern of Symptoms Derived from Seven Emotions. Results and Conclusions Seven Emotion give rise to various type of symptom. In special Anger cause more illness than other Seven Emotion.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.9-19
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• 2012

Virtual human used as HCI in digital contents expresses his various emotions across modalities like facial expression and body posture. However, few studies considered combinations of such nonverbal multimodal in emotion perception. Computational engine models have to consider how a combination of nonverbal modal like facial expression and body posture will be perceived by users to implement emotional virtual human, This paper proposes the impacts of nonverbal multimodal in design of emotion expressed virtual human. First, the relative impacts are analysed between different modals by exploring emotion recognition of modalities for virtual human. Then, experiment evaluates the contribution of the facial and postural congruent expressions to recognize basic emotion categories, as well as the valence and activation dimensions. Measurements are carried out to the impact of incongruent expressions of multimodal on the recognition of superposed emotions which are known to be frequent in everyday life. Experimental results show that the congruence of facial and postural expression of virtual human facilitates perception of emotion categories and categorical recognition is influenced by the facial expression modality, furthermore, postural modality are preferred to establish a judgement about level of activation dimension. These results will be used to implementation of animation engine system and behavior syncronization for emotion expressed virtual human.

• Korean Journal of Human Ecology
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• v.18 no.6
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• pp.1209-1219
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• 2009

The purpose of this study examined the path model of maternal emotional expression, temperament and self-esteem on emotion regulation among children. The subjects were 487 5th and 6th graders. Data was gathered through questionnaires reported by children and their mothers and analyzed by structural equation modeling. The results showed that children's 'activity level' temperament and maternal negative emotional expression directly affected maladaptive emotion regulation. Children's 'emotionality' temperament and maternal positive emotional expression directly affected adaptive emotion regulation. Children's 'approach-flexibility' temperament and self-esteem directly affected both maladaptive and adaptive emotion regulation. Maternal emotional expression and children's self-esteem mediated between children's temperament and emotion regulation. Additionally, the most important variable predicting children's maladaptive emotion regulation was the children's 'activity level' temperament, and the most important variable for adaptive emotion regulation was the children's 'emotionality' temperament.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.203-207
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• 2001

In this Paper, we propose the neural network based emotion recognition method for intelligently recognizing the human's emotion using CCD color image. To do this, we first acquire the color image from the CCD camera, and then propose the method for recognizing the expression to be represented the structural correlation of man's feature Points(eyebrows, eye, nose, mouse) It is central technology that the Process of extract, separate and recognize correct data in the image. for representation is expressed by structural corelation of human's feature Points In the Proposed method, human's emotion is divided into four emotion (surprise, anger, happiness, sadness). Had separated complexion area using color-difference of color space by method that have separated background and human's face toughly to change such as external illumination in this paper. For this, we propose an algorithm to extract four feature Points from the face image acquired by the color CCD camera and find normalization face picture and some feature vectors from those. And then we apply back-prapagation algorithm to the secondary feature vector. Finally, we show the Practical application possibility of the proposed method.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.224-230
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• 2010

As robots are no longer just working labors in the industrial fields, but stepping into the human's daily lives, interaction and communication between human and robot is becoming essential. For this social interaction with humans, emotion generation of a robot has become necessary, which is a result of very complicated process. Concept of mood has been considered in psychology society as a factor that effects on emotion generation, which is similar to emotion but not the same. In this paper, mood factors for robot considering not only the conditions of the robot itself but also the circumstances of the robot are listed, chosen and finally considered as elements defining a 2-dimensional mood space. Moreover, architecture that combines the proposed mood model and a emotion generation module is given at the end.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.146-149
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• 2003

This paper proposes the concept of “Artificial Emotion”(AE). The goal of AE is simulation, extension and expansion of natural emotion, especially human emotion. The object of AE is machine emotion and emotion machine. The contents of AE are emotion recognition, emotion measurement, emotion understanding emotion representation emotion generation, emotion processing, emotion control and emotion communication. The methodology, technology, scientific significance and application value of artificial emotion are discussed

• Journal of Integrative Natural Science
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• v.13 no.3
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• pp.97-104
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• 2020

This study suggests the emotion space modeling and emotion inference methods suitable for personalized services based on psychological and emotional models. For personalized emotion space modeling taking into account the subjective disposition based on the empirical assessment of the personal emotions felt by the personalization process of emotion space was used as a decision support tool, the Analytic Hierarchy Process. This confirmed that the special learning to perform personalized emotion space modeling without considering the subjective tendencies. In particular to check the possible reasoning based on fuzzy emotion space modeling and sensitivity for the quantification and vague human emotion to it based on the inherent human sensitivity.

• Proceedings of the ESK Conference
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• 1996.04a
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• pp.264-269
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• 1996

Facial expression is innate communication skill of human. Human can recognize theri psychological state by facial parameters which contain surface movement, color, humidity and etc. This study is to quantify or qualify human emotion by measurement of facial electromyography (EMG) and facial movement. The measurement is taken at the facial area of frontalis and zygomaticus The results is indicative to discriminate the positive and negative respond of emotion and to extract the parameter sensitive to positive and negative facial-expression. The facial movement according to EMG shows the possibility of non-invasive technique of human emotion.