• Title/Summary/Keyword: Recognizing Emotion

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A Statistical Approach for Recognizing Emotion from Dance Sequence

  • Park, Han-Hoon;Park, Jong-Il;Kim, Un-Mi;Woontack Woo
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.1161-1164
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    • 2002
  • We propose a simple method that can recognize human emotion from monocular dance image sequences. The method only exploits the information within image sequences and does not require cumbersome attachments like sensors. This makes the method a simple, human-friendly one. Moreover, the method is more robust and efficient by taking into account the statistical property of image sequences based on PCA (Principal Component Analysis). The correct recognition rate in real-time is about 75% in a variety of experiments.

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Recognizing Facial Expressions Using a Neural Network (신경망을 이용한 얼굴 표정인식)

  • 신영숙;이일병
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 1998.04a
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    • pp.101-105
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    • 1998
  • 기존의 표정인식 연구는 Ekman의 기본정서모형의 특에 의하여 표정인식이 이루어져왔다. 그러나 이러한 6가지 기본정서(행복, 놀람, 공포, 분노, 혐오, 슬픔)에 의한 표정인식은 6개 정서 중에서 선택하는 간제 선택법이 아닌 자유응답방식을 택했을때는 훨씬 인식률이 떨어진다. 이는 표정이 기본정서이외에도 여러 가지 미묘한 마음상태를 표현하고 있기 때문이다. 본 연구는 섬세한 표정인식을 우한 방법으로, 차원모형을 근거로 MLP를 적용한 표정인식을 수행하였다. 차원 모형에 의한 표정은 3가지 차원으로 하나의 표정을 이룬다. 3가지 차원은 쾌-불쾌, 각성-수면과 외부지향-내부지향이다. 3가지 차원을 갖는 각각의 표정은 MLP에 의하여 쾌-불쾌차원 68%, 각성-수면차원 60%, 외부지향-내부지향차원 76%의 인식률을 보였다. 연구결과에서 차원모형에 근거한 표정인식을 통하여 기존의 표정인식을 통하여 기존의 기본정서모형의 한계성을 극복하고 섬세한 표정인식을 수행할 수 있었다.

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Spreading Online Rumors: The Effects of Negative and Positive Emotions

  • Jong-Hyun Kim;Gee-Woo Bock;Rajiv Sabherwal;Han-Min Kim
    • Asia pacific journal of information systems
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    • v.30 no.1
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    • pp.1-20
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    • 2020
  • Malicious rumors often emerge online. However, few studies have examined why people spread online rumors. Recognizing that spreading online rumors is not only rational, but also emotional, this paper provides insights into the behavior of online rumor spreading using the cognitive emotion theory. The results show that perceived credibility of online rumors enhances both positive and negative emotions. However, positive emotions affect neither attitude nor behavior, whereas negative emotions affect both aspects of the spreading of online rumors. The results also indicate that prior positive attitude toward object influences negative emotions. Issues involvement moderates the relationship between attitude and behavior.

Human-Friendly Intelligent Hue Control System for Display Unit (디스플레이 장치의 인간 친화적인 지능형 색체 조절 시스템)

  • Seo, Jae-Yong;Kim, Jong-Won;Cho, Hyun-Chan
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.1
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    • pp.13-18
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    • 2007
  • Human's sight holds the most extents for recognizing information among other senses. If we make much better visualized environment for human, it will become more beneficial in person's emotion or body. Human is using a lot of display units in modern society. Basic hues ate Red, Green and Blue. Using these three colors, we can change hue sense and degree of brightness of display unit. If we control hue of unit to be suitable according to individual environment, we can feel comfortable or reduce stress. In this paper, we present Human-Friendly Intelligent Hue Control System(HFIHCS) that control hue of display unit using fuzzified factors related to human's emotion and environment. The effectiveness of the proposed system is demonstrated by questionnaire.

Development of an Emotion Recognition Robot using a Vision Method (비전 방식을 이용한 감정인식 로봇 개발)

  • Shin, Young-Geun;Park, Sang-Sung;Kim, Jung-Nyun;Seo, Kwang-Kyu;Jang, Dong-Sik
    • IE interfaces
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    • v.19 no.3
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    • pp.174-180
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    • 2006
  • This paper deals with the robot system of recognizing human's expression from a detected human's face and then showing human's emotion. A face detection method is as follows. First, change RGB color space to CIElab color space. Second, extract skin candidate territory. Third, detect a face through facial geometrical interrelation by face filter. Then, the position of eyes, a nose and a mouth which are used as the preliminary data of expression, he uses eyebrows, eyes and a mouth. In this paper, the change of eyebrows and are sent to a robot through serial communication. Then the robot operates a motor that is installed and shows human's expression. Experimental results on 10 Persons show 78.15% accuracy.

Emotion Recognition Method Using Heart-Respiration Connectivity (심장과 호흡의 연결성을 이용한 감성인식 방법)

  • Lee, Dong Won;Park, Sangin;Whang, Mincheol
    • Science of Emotion and Sensibility
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    • v.20 no.3
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    • pp.61-70
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    • 2017
  • Physiological responses have been measured to recognize emotion. Although physiological responses have been interrelated between organs, their connectivities have been less considered for emotion recognizing. The connectivities have been assumed to enhance emotion recognition. Specially, autonomic nervous system is physiologically modulated by the interrelated functioning. Therefore, this study has been tried to analyze connectivities between heart and respiration and to find the significantly connected variables for emotion recognition. The eighteen subjects(10 male, age $24.72{\pm}2.47$) participated in the experiment. The participants were asked to listen to predetermined sound stimuli (arousal, relaxation, negative, positive) for evoking emotion. The bio-signals of heart and respiration were measured according to sound stimuli. HRV (heart rate variability) and BRV (breathing rate variability) spectrum were obtained from spectrum analysis of ECG (electrocardiogram) and RSP (respiration). The synchronization of HRV and BRV spectrum was analyzed according to each emotion. Statistical significance of relationship between them was tested by one-way ANOVA. There were significant relation of synchronization between HRV and BRV spectrum (synchronization of HF: F(3, 68) = 3.605, p = 0.018, ${\eta}^2_p=0.1372$, synchronization of LF: F(3, 68) = 5.075, p = 0.003, ${\eta}^2_p=0.1823$). HF difference of synchronization between ECG and RSP has been able to classify arousal from relaxation (p = 0.008, d = 1.4274) and LF's has negative from positive (p = 0.002, d = 1.7377). Therefore, it was confirmed that the heart and respiration to recognize the dimensional emotion by connectivity.

Facial Expression Research according to Arbitrary Changes in Emotions through Visual Analytic Method (영상분석법에 의한 자의적 정서변화에 따른 표정연구)

  • Byun, In-Kyung;Lee, Jae-Ho
    • The Journal of the Korea Contents Association
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    • v.13 no.10
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    • pp.71-81
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    • 2013
  • Facial expressions decide an image for the individual, and the ability to interpret emotion from facial expressions is the core of human relations, hence recognizing emotion through facial expression is important enough to change attitude and decisions between individuals within social relations. Children with unstable attachment development, seniors, autistic group, ADHD children and depression group showed low performance results in facial expression recognizing ability tasks, and active interventions with such groups anticipates possibilities of prevention and therapeutic effects for psychological disabilities. The quantified figures that show detailed change in position of lips, eyes and cheeks anticipates for possible applications in diverse fields such as human sensibility ergonomics, korean culture and art contents, therapeutical and educational applications to overcome psychological disabilities and as methods of non-verbal communication in the globalizing multicultural society to overcome cultural differences.

Brain Activation to Facial Expressions Among Alcoholics (알코올 중독자의 얼굴 표정 인식과 관련된 뇌 활성화 특성)

  • Park, Mi-Sook;Lee, Bae Hwan;Sohn, Jin-Hun
    • Science of Emotion and Sensibility
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    • v.20 no.4
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    • pp.1-14
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    • 2017
  • The purpose of this study was to investigate the neural substrates for recognizing facial expressions among alcoholics by using functional magnetic resonance imaging (fMRI). Abstinent inpatient alcoholics (n=18 males) and demographically similar social drinkers (n=16 males) participated in the study. The participants viewed pictures from the Japanese Female Facial Expression Database (JAFFE) and evaluated intensity of facial expressions. the alcoholics had a reduced activation in the limbic areas including amygdala and hippocampus while recognizing the emotional facial expressions compared to the nonalcoholic controls. On the other hand, the alcoholics showed greater brain activations than the controls in the left lingual (BA 19)/fusiform gyrus, the left middle frontal gyrus (BA 8/9/46), and the right superior parietal lobule (BA 7) during the viewing of emotional faces. In sum, specific brain regions were identified that are associated with recognition of facial expressions among alcoholics. The implication of the present study could be used in developing intervention for alcoholism.

Development of Driver's Emotion and Attention Recognition System using Multi-modal Sensor Fusion Algorithm (다중 센서 융합 알고리즘을 이용한 운전자의 감정 및 주의력 인식 기술 개발)

  • Han, Cheol-Hun;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.6
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    • pp.754-761
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    • 2008
  • As the automobile industry and technologies are developed, driver's tend to more concern about service matters than mechanical matters. For this reason, interests about recognition of human knowledge and emotion to make safe and convenient driving environment for driver are increasing more and more. recognition of human knowledge and emotion are emotion engineering technology which has been studied since the late 1980s to provide people with human-friendly services. Emotion engineering technology analyzes people's emotion through their faces, voices and gestures, so if we use this technology for automobile, we can supply drivels with various kinds of service for each driver's situation and help them drive safely. Furthermore, we can prevent accidents which are caused by careless driving or dozing off while driving by recognizing driver's gestures. the purpose of this paper is to develop a system which can recognize states of driver's emotion and attention for safe driving. First of all, we detect a signals of driver's emotion by using bio-motion signals, sleepiness and attention, and then we build several types of databases. by analyzing this databases, we find some special features about drivers' emotion, sleepiness and attention, and fuse the results through Multi-Modal method so that it is possible to develop the system.

Artificial Intelligence and Literary Sensibility (인공지능과 문학 감성의 상호 연결)

  • Seunghee Sone
    • Science of Emotion and Sensibility
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    • v.26 no.4
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    • pp.115-124
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    • 2023
  • This study explores the intersection of literary studies and artificial intelligence (AI), focusing on the common theme of human emotions to foster complementary advancements in both fields. By adopting a comparative perspective, the paper investigates emotion as a shared focal point, analyzing various emotion-related concepts from both literary and AI perspectives. Despite the scarcity of research on the fusion of AI and literary studies, this study pioneers an interdisciplinary approach within the humanities, anticipating future developments in AI. It proposes that literary sensibility can contribute to AI by formalizing subjective literary emotions, thereby enhancing AI's understanding of complex human emotions. This paper's methodology involves the terminology-centered extraction of emotions, aiming to blend subjective imagination with objective technology. This fusion is expected to not only deepen AI's comprehension of human complexities but also broaden literary research by rapidly analyzing diverse human data. The study emphasizes the need for a collaborative dialogue between literature and engineering, recognizing each field's limitations while pursuing a convergent enhancement that transcends these boundaries.

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