• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 심포지엄 논문집 정보 및 제어부문
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• pp.132-134
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• 2004

Emotion recognition between human and human is done compositely using various features that are face, voice, gesture and etc. Among them, it is a face that emotion expression is revealed the most definitely. Human expresses and recognizes a emotion using complex and various features of the face. This paper proposes hybrid feature extraction for emotions recognition from facial expression. Hybrid feature extraction imitates emotion recognition system of human by combination of geometrical feature based extraction and color distributed histogram. That is, it can robustly perform emotion recognition by extracting many features of facial expression.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2011년도 추계학술대회
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• pp.104-105
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• 2011

• 디자인융복합연구
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• 제16권6호
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• pp.137-152
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• 2017

본 연구는 실버세대를 위한 컴패니언 로봇의 인터랙션 경험 디자인을 위해 사용자 태스크- 로봇 기능 적합도 매핑에 기반한 로봇 유형 분석과 멀티모달 대화 인터랙션에서의 로봇 감정표현 연구를 수행하였다. 노인의 니즈 분석을 위해 노인과 자원 봉사자를 대상으로 FGI, 에스노그래피를 진행하였으며 로봇 지원 기능과 엑추에이터 매칭을 통해 로봇 기능 조합 유형에 대한 분석을 하였다. 도출된 4가지 유형의 로봇 중 표정 기반 대화형 로봇 유형으로 프로토타이핑을 하였으며 에크만의 얼굴 움직임 부호화 시스템(Facial Action Coding System: FACS)을 기반으로 6가지 기본 감정에 대한 표정을 시각화하였다. 사용자 실험에서는 로봇이 전달하는 정보의 정서코드에 맞게 로봇의 표정이 변화할 때와 로봇이 인터랙션 사이클을 자발적으로 시작할 때 사용자의 인지와 정서에 미치는 영향을 이야기 회상 검사(Story Recall Test: STR)와 표정 감정 분석 소프트웨어 Emotion API로 검증하였다. 실험 결과, 정보의 정서코드에 맞는 로봇의 표정 변화 그룹이 회상 검사에서 상대적으로 높은 기억 회상률을 보였다. 한편 피험자의 표정 분석에서는 로봇의 감정 표현과 자발적인 인터랙션 시작이 피험자들에게 정서적으로 긍정적 영향을 주고 선호되는 것을 확인하였다.

• 대한가정학회지
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• 제40권10호
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• pp.103-112
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• 2002

This study investigated the relation between preschoolers' emotion understanding and parents' emotion expressiveness and attitude toward children's emotion expressiveness. Subjects were ninety 3- to 5-year old children and their parents. Parents' emotion socialization was measured by PACES developed by Saami(1989) and FEQ developed by Harberstadt(1986). And preschoolers' identification of basic emotional expressions and expression of their own feelings and others' feelings in various situations were measured. Results revealed that 5-year-old children understood emotion better than 3-year-old children, and mother's positive emotion expression influenced children's emotion understanding. The results are consistent with recent research showing that parents emotion socialization may be important for preschoolers' emotion understanding.

• 제어로봇시스템학회논문지
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• 제13권4호
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• pp.371-376
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• 2007

This paper presents an emotion recognition and its expression system of an intelligent robot like a home robot or a service robot. Emotion recognition method in the robot is used by a facial image. We use a motion and a position of many facial features. apply a tracking algorithm to recognize a moving user in the mobile robot and eliminate a skin color of a hand and a background without a facial region by using the facial region detecting algorithm in objecting user image. After normalizer operations are the image enlarge or reduction by distance of the detecting facial region and the image revolution transformation by an angel of a face, the mobile robot can object the facial image of a fixing size. And materialize a multi feature selection algorithm to enable robot to recognize an emotion of user. In this paper, used a multi layer perceptron of Artificial Neural Network(ANN) as a pattern recognition art, and a Back Propagation(BP) algorithm as a learning algorithm. Emotion of user that robot recognized is expressed as a graphic LCD. At this time, change two coordinates as the number of times of emotion expressed in ANN, and change a parameter of facial elements(eyes, eyebrows, mouth) as the change of two coordinates. By materializing the system, expressed the complex emotion of human as the avatar of LCD.

• 아동학회지
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• 제21권4호
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• pp.21-34
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• 2000

This investigation of developmental trends in children's emotional intelligence used the Emotional Intelligence Rating Scale for Preschool Children(Kim, 1998) to study 973 children. Significant age differences were found in 5 factors: 'utilization of emotion', 'regulation of emotion', 'handling of relationship between child and teacher' and 'handling of relationship with peers'. Children's emotional intelligence scores increased with age in 3 factors: 'utilization of emotion', 'empathy', and 'regulation of emotion'. Sex differences were found in 5 factors: 'utilization of emotion', 'empathy', 'appraisal and expression of self emotion', 'regulation of emotion', and 'handling of relationship between child and teacher'. In all factors, the scores of girls were higher than those the scores of boys.

• 디지털융복합연구
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• 제19권1호
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• pp.295-305
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• 2021

본 연구는 대학생의 분노표현, 대인관계문제의 관계를 파악한 후 매개효과로써 정서조절곤란에 대한 영향력을 확인하여 대인관계문제를 호소하는 대학생들을 이해하고 그들의 문제를 해결할 수 있는 프로그램 개발의 기초 자료를 제공하고자 실시되었다. 연구결과, 분노표현은 대인관계문제, 정서조절곤란에서 정적상관관계를 보였고, 대인관계문제는 정서조절곤란과 다소 높은 정적상관관계를 보였다. 또한, 대학생의 분노표현과 대인관계문제에서 정서조절곤란이 부분 매개하는 것을 확인하였다. 결론적으로 대학생들의 정서조절 곤란을 감소시키고 긍정적으로 분노표현을 하도록 이끄는 교육 프로그램 개발과 대인관계를 향상시킬 수 있는 중재 프로그램을 개발하는 것이 향후 연구에 필요함을 알 수 있었다.

• 한국HCI학회논문지
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• 제9권1호
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• pp.23-28
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• 2014

In this study we focus on the effect of the interaction between humans and reactive television when emotion recognition through facial expression mechanism is used. Most of today's user interfaces in electronic products are passive and are not properly fitted into users' needs. In terms of the user centered device, we propose that the emotion based reactive television is the most effective in interaction compared to other passive input products. We have developed and researched next generation cognitive TV models in user centered. In this paper we present a result of the experiment that had been taken with Fraunhofer IIS $SHORE^{TM}$ demo software version to measure emotion recognition. This new approach was based on the real time cognitive TV models and through this approach we studied the relationship between humans and cognitive TV. This study follows following steps: 1) Cognitive TV systems can be on automatic ON/OFF mode responding to motions of people 2) Cognitive TV can directly select channels as face changes (ex, Neutral Mode and Happy Mode, Sad Mode, Angry Mode) 3) Cognitive TV can detect emotion recognition from facial expression of people within the fixed time and then if Happy mode is detected the programs of TV would be shifted into funny or interesting shows and if Angry mode is detected it would be changed to moving or touching shows. In addition, we focus on improving the emotion recognition through facial expression. Furthermore, the improvement of cognition TV based on personal characteristics is needed for the different personality of users in human to computer interaction. In this manner, the study on how people feel and how cognitive TV responds accordingly, plus the effects of media as cognitive mechanism will be thoroughly discussed.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1175-1186
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• 2017

Human emotion recognition is one of the promising applications in the era of artificial super intelligence. Thus far, facial expression traits are considered to be the most widely used information cues for realizing automated emotion recognition. This paper proposes a novel facial expression recognition (FER) method that works well for recognizing emotion from image sequences. To this end, we develop the so-called weighted soft voting classification (WSVC) algorithm. In the proposed WSVC, a number of classifiers are first constructed using different and multiple feature representations. In next, multiple classifiers are used for generating the recognition result (namely, soft voting) of each face image within a face sequence, yielding multiple soft voting outputs. Finally, these soft voting outputs are combined through using a weighted combination to decide the emotion class (e.g., anger) of a given face sequence. The weights for combination are effectively determined by measuring the quality of each face image, namely "peak expression intensity" and "frontal-pose degree". To test the proposed WSVC, CK+ FER database was used to perform extensive and comparative experimentations. The feasibility of our WSVC algorithm has been successfully demonstrated by comparing recently developed FER algorithms.

• 디지털융복합연구
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• 제17권12호
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• pp.289-296
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• 2019

본 연구는 입원한 알콜의존환자가 지각하는 신체상, 정서표현신념 및 의사소통 능력의 정도와 상관관계를 파악하고 의사소통능력에 영향을 미치는 요인을 알아보기 위해 실시하였다. 자료 수집은 J시 소재 2개 정신전문병원과 S시에 소재한 1개 정신전문병원에 입원 중인 151명의 알코올의존 환자들을 대상으로 구조화된 설문지를 이용하였다. 자료수집 기간은 2018년 10월 11일부터 11월 20일 까지였다. 자료는 SPSS/WIN 21.0을 이용하여 T-test, ANOVA, 상관관계 분석과 다중회귀 분석을 사용하였다. 알코올의존 환자의 신체상과 정서표현 신념은 유의한 부적 상관관계, 신체상과 의사소통능력은 정적 상관관계가 있었고. 정서표현신념과 의사소통능력은 부적 상관관계가 있었다. 의사소통능력에 영향을 미치는 요인은 신체상, 학력, 정서표현신념이었고 총 설명력은 24.9%였다. 따라서 알코올의존환자의 의사소통 능력을 향상시키기 위하여 긍정적인 신체상을 가지도록하며 정서표현신념을 낮출 필요가 있다. 본 연구결과가 알코올 의사소통능력을 향상시키는데 기초자료로 활용될 수 있을 것이다.