• Annual Conference of KIPS
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• 2013.11a
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• pp.1476-1478
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• 2013

최근 페이스북(Facebook), 트위터(Twitter) 등의 SNS(Social Network Service)의 사용자가 급격하게 증가하고 있다. SNS가 발달하면서 언제 어디서나 쉽게 자신의 위치, 현재의 감정들을 온라인상에서 공유한다. 이에 따라 사람의 감정을 표현하는 단어 100여개를 7가지 감정(기쁨, 흥미, 슬픔, 분노, 놀람, 지루함, 통증)으로 분류하였으며[1]. 이를 분석하기 위한 감정 표현 분석기 모듈을 설계하였다. 설계한 모듈을 사용하여 페이스북의 사용자 뉴스피드(News-Feed)를 분석하여 사용자의 성향을 분석하였다.

• Cross-Cultural Studies
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• v.51
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• pp.329-356
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• 2018

Types of emotional expressions are comprised of vocabulary that describes emotion and composition of sentences to express emotion such as an exclamatory sentence and a rhetorical question, expressions of interjection, adverbs of attitude for an idea, and a style of writing. This study is focused on vocabulary that describes emotion and analyzes the aspect of translation when emotional expression of 'Kyo(驚)' is shown in "Kokoro". As a result, the aspect of translation for expression of 'Kyo(驚)' showed that it was translated to vocabulary as suggested in the dictionary in some cases. However, it was not always translated as suggested in the dictionary. Vocabulary that describes the emotion of 'Kyo(驚)' in Japanese sentences is mostly translated to corresponding parts of speech in Korean. Some adverbs needed to add 'verbs' when they were translated. Different vocabulary was added or used to maximize emotion. However, the corresponding part of speech in English was different from Korean. Examples of Japanese sentences expressing 'Kyo(驚)' by verbs were translated to expression of participles for passive verbs such as 'surprise' 'astonish' 'amaze' 'shock' 'frighten' 'stun' in many cases. Idioms were also translated with focus on the function of sentences rather than the form of sentences. Those expressed in adverbs did not accompany verbs of 'Kyo(驚)'. They were translated to expression of participles for passive verbs and adjectives such as 'surprise' 'astonish' 'amaze' 'shock' 'frighten' 'stun' in many cases. Main agents of emotion were showat the first person and the third person in simple sentences. Translation of emotional expressions when a main agent was the first person showed that the fundamental word order of Japanese was translated as in Korean. However, adverbs of time and adverbs of degree were ended to be added. The first person as the main agent of emotion was positioned at the place of subject when it was translated in English. However, things or causes of events were positioned at the place of subject in some cases to show the degree of 'Kyo(驚)' which the main agent experienced. The expression of conjecture and supposition or a certain visual and auditory basis was added to translate the expression of emotion when the main agent of emotion was the third person. Simple sentences without the main agent of emotion showed that their subjects could be omitted even if they were essential components because they could be known through context in Korean. These omitted subjects were found and translated in English. Those subjects were not necessarily human who was the main agent of emotion. They could be things or causes of events that specified the expression of emotion.

• Sleep Medicine and Psychophysiology
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• v.7 no.2
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• pp.109-114
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• 2000

Objectives: This study was performed to examine the characteristic cardiovascular response patterns associated with the imagination and discussion of anger-provoked events in patients with hwa-byung. Methods: Forty-three female patients with hwa-byung were evaluated with the Korean version of the State-Trait Anger Expression Inventory, the State-Trait Anxiety Inventory, Hamilton Rating Scale for Anxiety, Beck Depression Inventory, and Hamilton Rating Scale for Depression just before the task. Subjective Units of Distress (SUDS) and Vividness of the event (VIVID) during the imagination and discussion of the event were evaluated immediately after tasks. Blood pressure (BP) and heart rate (HR) during baseline, rest, and tasks were also evaluated. Results: Both startle and recovery responses of BP, startle response of HR, SUDS, and VIVID in discussion task were significantly larger than in the imagination task. Conclusion: Results suggest that it is undesirable for the patients to excessively and repeatedly recall and talk about the anger events.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.70-80
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• 2013

The purpose of this study has placed its meaning in the use as the basic material for the research of the person's facial expressions, by researching and analyzing the visual reactions of recognition of children according to the facial expressions of emotion and by surveying the verbal reactions of boys and girls according to the individual expressions of emotion. The subjects of this study were 108 children at the age of 6 - 8 (55 males, 53 females) who were able to understand the presented research tool, and the response survey conducted twice were used in the method of data collection by individual interviews and self administered questionnaires. The research tool using in the questionnaires were classified into 6 types of joy, sadness, anger, surprise, disgust, and fear which could derive the specific and accurate responses. Regarding children's visual reactions of recognition, both of boys and girls showed the high frequency in the facial expressions of joy, sadness, anger, surprise, and the low frequency in fear, disgust. Regarding verbal reactions, it showed the high frequency in the heuristic responses either to explore or the responds to the impressive parts reminiscent to the facial appearances in all the joy, sadness, anger, surprise, disgust, fear. And it came out that the imaginary responses created new stories reminiscent to the facial expression in surprise, disgust, and fear.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.83-100
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• 2023

This study determines whether the perception of the frequency of experiencing positive, negative, and surprise emotions changes according to the level of cognitive well-being. Furthermore, we determined practical means to analyze which emotions can be managed in daily life as an effective means of improving overall life satisfaction by identifying representative specific emotions that strongly predict the level of cognitive well-being. To this end, the between-subjects factorial design is adopted to measure the frequency of emotional experiences according to the level of cognitive well-being in 438 university undergraduate students. For cognitive well-being, the life satisfaction scale (SWLS) was used, and the PANAS-X scale was used to measure emotional frequency. As a result, first, the group with high cognitive well-being displays a higher frequency of positive and surprise emotional experiences and a lower frequency of negative emotional experiences than the group with low cognitive well-being. Second, the results confirm that representative emotions affecting cognitive well-being included 8 positive emotions, 7 negative emotions, and 1 surprise emotion. Among them, positive emotions include "happy" and "confident," negative emotions include "dissatisfied with self" and "disgusted with self," and surprise emotions include words such as "amazed." Therefore, we can conclude that the representative emotions are those with the greatest influence on cognitive well-being. Therefore, increasing the frequency of specific emotions (e.g., happy, confident, and surprise) and decreasing the frequency of others (e.g., dissatisfied with self and disgusted with self) could be effective in improving cognitive well-being than unconditionally examining emotions experienced in daily life.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.21-26
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• 2002

This paper presents the new approach of identifying human emotional states such as anger, happiness, normal, sadness, or surprise. This is accomplished by using discrete duration continuous hidden Markov models(DDCHMM). For this, the emotional feature parameters are first defined from input speech signals. In this study, we used prosodic parameters such as pitch signals, energy, and their each derivative, which were then trained by HMM for recognition. Speaker adapted emotional models based on maximum a posteriori(MAP) estimation were also considered for speaker adaptation. As results, the simulation performance showed that the recognition rates of vocal emotion gradually increased with an increase of adaptation sample number.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.375-384
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• 2011

This paper suggests a method to recognize facial expressions of animation characters by means of dominant colors and feature points. The proposed method defines a simplified mesh model adequate for the animation character and detects its face and facial components by using dominant colors. It also extracts edge-based feature points for each facial component. It then classifies the feature points into corresponding AUs(action units) through neural network, and finally recognizes character facial expressions with the suggested AU specification. Experimental results show that the suggested method can recognize facial expressions of animation characters reliably.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.537-540
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• 2005

본 논문에서는 사람의 감정, 건강상태, 정신상태등 다양한 정보를 포함하고 있는 웃음, 슬픔, 졸림, 놀람, 윙크, 무표정 등의 표정을 인식하기 위한 표정의 특징이 되는 얼굴의 국부적 요소인 눈과 입을 검출하여 표정의 특징을 추출한다. 표정 특징의 추출을 위한 전체적인 알고리즘 과정으로는 입력영상으로부터 칼라 정보를 이용하여 얼굴 영역을 검출하여 얼굴에서 특징점의 위치 정보를 이용하여 국부적 요소인 특징점 눈과 입을 추출한다. 이러한 특징점 추출 과정에서는 에지, 이진화, 모폴로지, 레이블링 등의 전처리 알고리즘을 적용한다. 레이블 영역의 크기를 이용하여 얼굴에서 눈, 눈썹, 코, 입 등의 1차 특징점을 추출하고 누적 히스토그램 값과 구조적인 위치 관계를 이용하여 2차 특징점 추출 과정을 거쳐 정확한 눈과 입을 추출한다. 표정 변화에 대한 표정의 특징을 정량적으로 측정하기 위해 추출된 특징점 눈과 입의 눈과 입의 크기와 면적, 미간 사이의 거리 그리고 눈에서 입까지의 거리 등 기하학적 정보를 이용하여 6가지 표정에 대한 표정의 특징을 추출한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.2
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• pp.97-102
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• 2002

In this paper, we propose the technique for recognizing the human s emotion by using the CCD color image. To do this, we first get the face image by using skin-color from the original color image acquired by the CCD camera. And we propose the method for finding man s feature points(eyebrows, eye, nose, mouse) from the face image and the geometrical method for recognizing human s emotion (surprise, anger, happiness, sadness) from the structural correlation of man s feature feints. The proposed method in this paper recognize the human s emotion by learning the neural network. Finally, we have proven the effectiveness of the Proposed method through the experimentation.

• Science of Emotion and Sensibility
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• v.2 no.2
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• pp.43-52
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• 1999

정서는 생리적 반응을 수반하는 주관적인 경험이다. 뇌파와 자율신경계 반응의 차이에 의한 기본정서 구분 연구는 보고된 바가 없다. 본 연구에서는 1) 여섯 기본정서를 뚜렷하게 유발하는 정서자극을 선정하고, 이를 사용하여 2) 기본정서를 구분할 수 있는 심리생리적 복합 지표 모델을 개발하고자 하였다. 국제정서사진체계에서 여섯 기본정서 (행복, 슬픔, 분노, 혐오, 공포, 놀람) 각각을 신뢰롭게 유발하는 여섯 쌍의 슬라이드를 선택하였다. 슬라이드 제시에 의하여 유발되는 뇌파, 심전도, 호흡, 피부전기반응을 기록하여 분석/비교하였다. 주요결과를 요약하면 다음과 같다. 첫째, 뇌파의 상태적 출현량, 심박률, 호흡률, 피부전도반응은 안정상태와 정서상태간의 비교에서 유의미한 차이가 나타났다. 둘째, 뇌파분석결과에서는 theta (F4, 01), slow alpha (F3, F4), fast alpha (O2), fast beta (F4, O2)파의 상대적 출현량 변화값이 일부 정서들간에 유의미한 차이가 있었다. 셋째, 자율신경계 분석결과에서는 심박률, 호흡률, 피부전도반응이 일부 정서들간에 유의미한 차이를 보여주었다. 이들 결과를 토대로 기본정서를 특정적으로 구분할 수 있는 심리생리적 복합 지표 모델을 구성하였다. 네 기본정서 (공포, 혐오, 슬픔, 분노)는 뇌파와 자율신경계 반응패턴에 의한 구분이 가능하였으나, 행복과 놀람은 본 연구에서 사용한 심리생리지표에 의한 최종 구분이 불가능하였다. 여섯 기본정서를 모두 구분할 수 있는 적절한 지표를 찾아내는 후속연구가 필요하다.