• 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 the Semiconductor & Display Technology
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• v.12 no.3
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• pp.53-57
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• 2013

Human emotions are expressed in various ways. It can be expressed through language, facial expression and gestures. In particular, the facial expression contains many information about human emotion. These vague human emotion appear not in single emotion, but in combination of various emotion. This paper proposes a emotional expression algorithm using Active Appearance Model(AAM) and Fuzz k- Nearest Neighbor which give facial expression in similar with vague human emotion. Applying Mahalanobis distance on the center class, determine inclusion level between center class and each class. Also following inclusion level, appear intensity of emotion. Our emotion recognition system can recognize a complex emotion using Fuzzy k-NN classifier.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.1-11
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• 2014

This paper addresses the emotion computing model for software affective agents. In this paper, emotion is represented in valence-arousal-dominance dimensions instead of discrete categorical representation approach. Firstly, a novel emotion model architecture for affective agents is proposed based on Scherer's componential theories of human emotion, which is one of the well-known emotion models in psychological area. Then a fuzzy logic is applied to determine emotional statuses in the emotion model architecture, i.e., the first valence and arousal, the second valence and arousal, and dominance. The proposed methods are implemented and tested by applying them in a virtual training system for children's neurobehavioral disorders.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1281-1285
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• 2004

There are numerous emotions in the human world. Human expresses and recognizes their emotion using various channels. The example is an eye, nose and mouse. Particularly, in the emotion recognition from facial expression they can perform the very flexible and robust emotion recognition because of utilization of various channels. Hybrid-feature extraction algorithm is based on this human process. It uses the geometrical feature extraction and the color distributed histogram. And then, through the independently parallel learning of the neural-network, input emotion is classified. Also, for the natural classification of the emotion, advancing two-dimensional emotion space is introduced and used in this paper. Advancing twodimensional emotion space performs a flexible and smooth classification of emotion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.155-161
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• 2014

This study presents the real-time emotion image contents player to induce the user's emotion efficiently. The emotion image contents player was designed to efficiently induce by giving a change in the color, brightness, saturation of image contents corresponded to the user's emotion. In the emotion recognition module, physiological signal of pulse, skin temperature, skin resistance which based on autonomic nervous system were used. The emotion recognition part used physiological signal of pulse, skin temperature, skin resistance based on autonomic nervous system. The image as emotional contents was used with the 9 kinds emotion area classified in international affective picture system(IAPS). As experimental results, the use's emotion that match the image's emotion with the emotion image contents player was derived 10% more accurately. The emotion contents player is expected to increase emotional feeling between users's emotion and contents emotion duo to the real-time emotion reflection.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.611-614
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• 2001

Voice is one of the most efficient communication media and it includes several kinds of factors about speaker, context emotion and so on. Human emotion is expressed is expressed in the speech, the gesture, the physiological phenomena(the breath, the beating of the pulse, etc). In this paper, the emotion recognition method model using neuro-fuzzy in order to have cognizance of emotion from voice signal is presented and simulated.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2012.05a
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• pp.63-64
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• 2012

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.276-279
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• 2003

Generally, it is known that human beings have both emotion and rationality. Especially, emotion is so subjective that human beings might act in different way for the same environment according to their own emotion. Emotion also plays very important role in communication with someone else. For an agent, even though it is designed to act delicately, when it is designed without internal emotion, it can not interact dynamically just like human beings. In this paper, we suggest an agent which action is effected by not only rationality but also emotion to make it interact with human beings dynamically. It is composed of supervised learning, SOM (Self-Organizing Map) and fuzzy decision.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.648-653
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• 2007

Researches on artificial emotion which generates emotion artificially from various external excitations imitating human emotion has been initiated in recent years. But the conventional studies in which the emotion state is changed exponentially or linearly by external emotion excitation have a drawback that the variation of emotion state is changed rapidly and abruptly. In this paper, we propose an artificial emotion generation model which reflects not only strength and frequency of external emotion excitations but also period of it in the emotion state and represents the emotion state with a sigmoid curve w.r.t. time. And we propose an artificial emotion system which generates emotion at the situation of no external emotional excitations through recollection of past emotional excitations, and show its effectiveness through computer simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2373-2378
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• 2005

An emotion detection algorithm using frontal facial image is presented in this paper. The algorithm is composed of three main stages: image processing stage and facial feature extraction stage, and emotion detection stage. In image processing stage, the face region and facial component is extracted by using fuzzy color filter, virtual face model, and histogram analysis method. The features for emotion detection are extracted from facial component in facial feature extraction stage. In emotion detection stage, the fuzzy classifier is adopted to recognize emotion from extracted features. It is shown by experiment results that the proposed algorithm can detect emotion well.