• Title/Summary/Keyword: Human emotion

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Sijo Literature Therapeutic Research on the Structuring of Emotion-DNA

  • Park, In-Kwa
    • International Journal of Advanced Culture Technology
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    • v.5 no.1
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    • pp.26-31
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    • 2017
  • In this study, Emotion-DNA is constructed in the same way asthat the human DNA constructs the human body. Emotion-DNA is copied and translated in the same way as that the human DNA copies and translates itself. We made an attempt to embody the mind by Emotion-DNA like the symbols "A, T, G, C, U" that make up the chromosome of the human body. This is a diagram of the flow of emotions that the human body operates by literary works. These schemes present new directions for the therapeutic analysis of literary works and for the creation of therapeutic literary works. In this study, we analyzed the nominal Emotion-syllables as a framework of the structuring of emotional DNA. As a result, through the structuring of the emotional DNA, it was judged that the therapeutic action of the human body, which is included in the Rated Sijo among the literary works, can be more concrete and powerful than the works of other genres.

Human emotional elements and external stimulus information-based Artificial Emotion Expression System for HRI (HRI를 위한 사람의 내적 요소 기반의 인공 정서 표현 시스템)

  • Oh, Seung-Won;Hahn, Min-Soo
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.7-12
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    • 2008
  • In human and robot interaction, the role of emotion becomes more important Therefore, robots need the emotion expression mechanism similar to human. In this paper, we suggest a new emotion expression system based on the psychological studies and it consists of five affective elements, i.e., the emotion, the mood, the personality, the tendency, and the machine rhythm. Each element has somewhat peculiar influence on the emotion expression pattern change according to their characteristics. As a result, although robots were exposed to the same external stimuli, each robot can show a different emotion expression pattern. The proposed system may contribute to make a rather natural and human-friendly human-robot interaction and to promote more intimate relationships between people and robots.

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Study for Variational Characteristics of Brain According to Human Emotion -Human Emotion by Auditory Perception- (감성에 따른 뇌의 변화 특성에 대한 연구 -청각감각에 의한 감성-)

  • Whang, Min-Cheol;Sohn, Jin-Hun;Kim, Chul-Jung
    • Journal of Korean Institute of Industrial Engineers
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    • v.23 no.3
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    • pp.609-619
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    • 1997
  • The concept of human emotion is recently demanded to be imbedded in industrial product and environment for enhancing quality of life. Human emotion is attempted to be qualified and quantified by physiological measurements. EEG variation, one of the physiological measurement, is observed to characterize psychological response in this study. This study is to find function and process of brain according to emotion. Twenty university students participated in this study and experienced positive and negative emotion by auditory stimulus. Delta, theta, alpha and beta waves showed characteristic variation in normalized sense according to positive and negative emotion. Local area showing significant difference between positive and negative emotion decreases with stimulus duration. Delta, theta and beta waves increase with negative emotion while alpha wave does with positive emotion.

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Dynamic Emotion Classification through Facial Recognition (얼굴 인식을 통한 동적 감정 분류)

  • Han, Wuri;Lee, Yong-Hwan;Park, Jeho;Kim, Youngseop
    • 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.

Emotional Expression System Based on Dynamic Emotion Space (동적 감성 공간에 기반한 감성 표현 시스템)

  • Sim Kwee-Bo;Byun Kwang-Sub;Park Chang-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.1
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    • pp.18-23
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    • 2005
  • It is difficult to define and classify human emotion. These vague human emotion appear not in single emotion, but in combination of various emotion. And among them, a remarkable emotion is expressed. This paper proposes a emotional expression algorithm using dynamic emotion space, which give facial expression in similar with vague human emotion. While existing avatar express several predefined emotions from database, our emotion expression system can give unlimited various facial expression by expressing emotion based on dynamically changed emotion space. In order to see whether our system practically give complex and various human expression, we perform real implementation and experiment and verify the efficacy of emotional expression system based on dynamic emotion space.

Human Emotion Recognition based on Variance of Facial Features (얼굴 특징 변화에 따른 휴먼 감성 인식)

  • Lee, Yong-Hwan;Kim, Youngseop
    • Journal of the Semiconductor & Display Technology
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    • v.16 no.4
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    • pp.79-85
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    • 2017
  • Understanding of human emotion has a high importance in interaction between human and machine communications systems. The most expressive and valuable way to extract and recognize the human's emotion is by facial expression analysis. This paper presents and implements an automatic extraction and recognition scheme of facial expression and emotion through still image. This method has three main steps to recognize the facial emotion: (1) Detection of facial areas with skin-color method and feature maps, (2) Creation of the Bezier curve on eyemap and mouthmap, and (3) Classification and distinguish the emotion of characteristic with Hausdorff distance. To estimate the performance of the implemented system, we evaluate a success-ratio with emotional face image database, which is commonly used in the field of facial analysis. The experimental result shows average 76.1% of success to classify and distinguish the facial expression and emotion.

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Ahn Min-young's Jade-like Sijo, Emotion Coding by Orchid

  • Park, Inkwa
    • International Journal of Advanced Culture Technology
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    • v.7 no.1
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    • pp.199-208
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    • 2019
  • Today, mankind is falling in serious stress. So there are various way that heal men as human psychology, philosophy, medical science etc. And in recent years, interest in literature therapy has been focused to heal the human sense of spirit. In the future, we will be able to treat our spirit sense with AI Emotion. The treatment process can be induced by the system of emotion coding which AI Emotion deliver Emotion signals to Human body. For this study, we used the Ahn Min-young's Sijo. The reason is that his Sijo is useful this study of the Emotion Coding. As the result, Ahn Min-young's emotion coding created the codes as if amino acid codes. We must continue this research. Then our literature therapy could grow and contribute to human well-being.

Emotion Recognition based on Tracking Facial Keypoints (얼굴 특징점 추적을 통한 사용자 감성 인식)

  • Lee, Yong-Hwan;Kim, Heung-Jun
    • Journal of the Semiconductor & Display Technology
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    • v.18 no.1
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    • pp.97-101
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    • 2019
  • Understanding and classification of the human's emotion play an important tasks in interacting with human and machine communication systems. This paper proposes a novel emotion recognition method by extracting facial keypoints, which is able to understand and classify the human emotion, using active Appearance Model and the proposed classification model of the facial features. The existing appearance model scheme takes an expression of variations, which is calculated by the proposed classification model according to the change of human facial expression. The proposed method classifies four basic emotions (normal, happy, sad and angry). To evaluate the performance of the proposed method, we assess the ratio of success with common datasets, and we achieve the best 93% accuracy, average 82.2% in facial emotion recognition. The results show that the proposed method effectively performed well over the emotion recognition, compared to the existing schemes.

Emotion Coding of Sijo Crying Cuckoo at the Empty Mountain (시조 「공산에 우는 접동」의 감정 코딩)

  • Park, Inkwa
    • The Journal of the Convergence on Culture Technology
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    • v.5 no.1
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    • pp.13-20
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    • 2019
  • This study aims to study the codes that can code the Sijo's emotional codes into AI and use them in literature therapy. In this study, we conducted emotional coding of the Sijo Crying Cuckoo at the Empty Mountain. As a result, the Emotion Codon was able to indicate the state of sadness catharsis. This implanting of the Sijo's emotional codes into Emotion Codon is like implanting human emotions into AI. If the basic emotion codes are implanted in the Emotion Codon and induced of AI's self-learning, We think AI can combine various emotions that occur in the human body. AI can then replace human emotions, which can be useful in treating of human emotions. It is believed that continuing this study will induce human emotions to heal the mind and spirit.

Hybrid-Feature Extraction for the Facial Emotion Recognition

  • Byun, Kwang-Sub;Park, Chang-Hyun;Sim, Kwee-Bo;Jeong, In-Cheol;Ham, Ho-Sang
    • 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.

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