• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.3
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• pp.167-179
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• 2016

Online games, by a massive influx of many players, it has diverse situations in which emotion is generated. Emotion plays an important role that helps players to interact and immerse in game. In the previous games, simple structures are used to express emotion. By increasing the user's needs of emotion in the game, it is necessary to structure a various type of emotion. In this paper, the game components were classified as background, object, and character in order to analyze emotion structurally in game. We defined how to use the rule of emotion, and applied to League of legend, Cyphers and World of Warcraft which belong to the AOS genre. The AOS game is well-suited for analyzing emotion structure, because a various emotional changes and situations can arise in the game. Through this paper, it was discovered similarities emotion to be used in online games. It is expected to generalize the emotion in the game by analyzing the emotional structure of more games in future.

• Science of Emotion and Sensibility
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• v.14 no.2
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• pp.257-268
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• 2011

We define a 'dominant emotion' as acting dominantly for unit time, and propose methodology to extract dominant emotion in a literature automatically. Due to the nature of the Korean language, it is able to be changed or reversed owns meanings as desinence. But it might be possible to extract a dominant emotion in a text has a small quantity like a fiction or an essay. A process to extract a dominant emotion in a literature is as follows. At first, extract morphemes in a whole text. And dispart words having emotional meaning as matching emotion terms database. Map disported terms to a affective circumplex model and matching it with basic emotion. Finally, analyze dominant emotion according to matched basic emotion. And we adjust our methodology to two literature; modem fiction 'A lucky day' by Jingeon, Hyun and essay 'An old man who shave a bat' by Woyoung, Yun. As a result, it was possible to grasp flows of dominant emotion.

• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.400-414
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• 2018

It is required for today's video contents to interact with a viewer in order to provide more personalized experience to viewer(s) than before. In order to do so by providing friendly experience to a viewer from video contents' systemic perspective, understanding and analyzing the situation of the viewer have to be preferentially considered. For this purpose, it is effective to analyze the situation of a viewer by understanding the state of the viewer based on the viewer' s behavior(s) in the process of watching the video contents, and classifying the behavior(s) into the viewer's emotion and state during the flow. The term 'Flow-emotion-state' presented in this study is the state of the viewer to be assumed based on the emotions that occur subsequently in relation to the target video content in a situation which the viewer of the video content is already engaged in the viewing behavior. This Flow-emotion-state of a viewer can be expected to be utilized to identify characteristics of the viewer's Flow-situation by observing and analyzing the gesture and the facial expression that serve as the input modality of the viewer to the video content.

• The Pure and Applied Mathematics
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• v.24 no.4
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• pp.227-241
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• 2017

The study investigates the stock market using emotion index calculated from SMD based on investors' emotion. In the VAR anlaysis, we find that the correlation between the KOSPI200 return and emotion score sum is highest in 2- or 3- day lag. This study concludes that explanatory power of the SMD emotion index is limited in explaining the Korean stock market yet.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.33-39
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• 2010

The interaction of emotion is an important factor in Human-Robot Interaction(HRI). This requires a contextual appraisal of emotion extracting the emotional information according to the events happened from past to present. In this paper an emotion appraisal system based on the cognitive context is presented. Firstly, a conventional emotion appraisal model is simplified to model a contextual emotion appraisal which defines the types of emotion appraisal, the target of the emotion induced from analyzing emotional verbs, and the transition of emotions in the context. We employ a language based cognitive system and its sentential memory and object descriptor to define the type and target of emotion and to evaluate the emotion varying with the process of time with the a priori emotional evaluation of targets. In a experimentation, we simulate the proposed emotion appraisal system with a scenario and show the feasibility of the system to HRI.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1598-1603
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• 2013

Recently, researches on analyzing relationship between the state of emotion and musical stimuli are increasing. In many previous works, data sets from all extracted channels are used for pattern classification. But these methods have problems in computational complexity and inaccuracy. This paper proposes a selection of optimal EEG channel to reflect the state of emotion efficiently according to music listening by analyzing stochastic feature vectors. This makes EEG pattern classification relatively simple by reducing the number of dataset to process.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1363-1368
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• 2015

Recently, computer form were smaller than before because of computing technique's development and many wearable device are formed. So, computer's cognition of human emotion has importantly considered, thus researches on analyzing the state of emotion are increasing. Human voice includes many information of human emotion. This paper proposes a discriminative feature vector selection for emotion classification based on speech. For this, we extract some feature vectors like Pitch, MFCC, LPC, LPCC from voice signals are divided into four emotion parts on happy, normal, sad, angry and compare a separability of the extracted feature vectors using Bhattacharyya distance. So more effective feature vectors are recommended for emotion classification.

• Science of Emotion and Sensibility
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• v.17 no.1
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• pp.53-62
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• 2014

Despite the huge potential of the practical application of emotion recognition technologies, the enhancement of the technologies still remains a challenge mainly due to the difficulty of recognizing emotion. Although not perfect, human emotions can be recognized through human images and sounds. Emotion recognition technologies have been researched by extensive studies that include image-based recognition studies, sound-based studies, and both image and sound-based studies. Studies on emotion recognition through facial expression detection are especially effective as emotions are primarily expressed in human face. However, differences in user environment and their familiarity with the technologies may cause significant disparities and errors. In order to enhance the accuracy of real-time emotion recognition, it is crucial to note a mechanism of understanding and analyzing users' personality traits that contribute to the improvement of emotion recognition. This study focuses on analyzing users' personality traits and its application in the emotion recognition system to reduce errors in emotion recognition through facial expression detection and improve the accuracy of the results. In particular, the study offers a practical solution to users with subtle facial expressions or low degree of emotion expression by providing an enhanced emotion recognition function.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.66-69
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• 2008

본 연구에서는 포레스터 그룹에서 제시한 커뮤니티 활용그룹을 중심으로, 실험 참여자 12명을 섭외하여 사용자 조사를 진행한후, 정성적 분석을 진행하였다. 그 과정에서 슈나이더만의 네트웍을 활용하는 4가지 주요 행동들을 대입하여 이에 해당하는 행위들을 파악할 수 있도록 프레임웍을 갖추었다. 결과로 이들의 행동들이 6가지로 차이를 분명하게 나타내고 있으며 이를 통해 사용자 연구에서의 정성적 분석이 구체적 근거를 가질 수 있음을 검증하였다. 본 논문은 사용자 조사를 통해 연구를 진행하는 과정에서 섭외된 사용자의 객관적 검증을 위해 연구자의 성향을 조사할 수 있는 프레임웍을 반영하여 신뢰도를 높일 수 있음을 케이스 스터디로 연구하였다.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.473-476
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• 1997

Human visual emotion were investigated by analyzing HRV from ECG signals, which were varied by the visual stimuli. In this paper, twelve university students experienced visual emotion by pictures from IAPS. ECG and subjective rating were obtained for human emotion evaluation. For determination of HRV, ECG was extracted into HF and LF via power spectrum analysis. The results showed that HRV is good for discrimination between positive and negative emotions.