• Science of Emotion and Sensibility
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• v.19 no.2
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• pp.3-18
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• 2016

This research, through video-based communication in a social video platform environment, studied the influence of the relationship between a video-watching subject and other watchers to that of the user's positive emotion and sense of community. Based on prior psychological theories called Social Impact Theory and Self-Monitoring Theory, the research built an actual video-based social video platform environment in order to verify an alternative utilizing new means of interaction based on videos. The result shows that under video-watching settings, user feels greater positive emotion and sense of community when the screen shows other people's reaction live and when him or her self's face is shown together, compared to when they are not shown. Also, based on the ANOVA analysis, the percentage of increase in positive emotion was greater when the two conditions mentioned above were provided synchronously compared to when they were not. The result of the research is expected to yield insights about a new form of social video platform.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.653-662
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• 2006

In ubiquitous computing that is to build computing environments to provide proper services according to user's context, human being's emotion recognition based on facial expression is used as essential means of HCI in order to make man-machine interaction more efficient and to do user's context-awareness. This paper addresses a problem of rigidly basic emotion recognition in context-sensitive facial expressions through a new Bayesian classifier. The task for emotion recognition of facial expressions consists of two steps, where the extraction step of facial feature is based on a color-histogram method and the classification step employs a new Bayesian teaming algorithm in performing efficient training and test. New context-sensitive Bayesian learning algorithm of EADF(Extended Assumed-Density Filtering) is proposed to recognize more exact emotions as it utilizes different classifier complexities for different contexts. Experimental results show an expression classification accuracy of over 91% on the test database and achieve the error rate of 10.6% by modeling facial expression as hidden context.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.05a
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• pp.57-60
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• 2011

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.9
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• pp.215-223
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• 2017

Various methods for creating interesting games are used in the development process. Because the empirical part is difficult to measure and analyze, it usually only measures and analyzes the parts where data are easy to quantify. This is a clear limit to the fact that the experience of the game is important.This study proposes a system that recognizes the face of a game user and measures the emotion change from the recognized information in order to easily quantify the experience of the user who is playing the game. The system recognizes emotions and records them in real time from the face of the user who is playing the game. These recorded data include time and figures related to the progress of the game, and numerical values for emotions recognized from the face. Using the recorded data, it is possible to judge what kind of emotion the game induces to the user at a certain point in time. Numerical data on the recorded empirical part using the system of this study is expected to help develop the game according to the developer 's intention.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.337-342
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• 2010

The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. So users are tend to build play-list for manage songs. However the manual selection of songs for creating play-list is bothersome task. This paper proposes an auto play-list recommendation system considering user's context of use and preference. This system has two separate systems: mood and emotion classification system and music recommendation system. Users need to choose just one seed song for reflection their context of use and preference. The system recommends songs before the current song ends in order to fill up user play-list. User also can remove unsatisfied songs from recommended song list to adapt user preferences of the system for the next recommendation precess. The generated play-lists show well defined mood and emotion of music and provide songs that user preferences are reflected.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2007.05a
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• pp.114-117
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• 2007

사용자의 감성을 측정하기 위한 심리적 측정방법 중에서 사용자가 느끼는 감성을 형용사와 같은 어휘를 통해 간접적으로 측정하는 방법, 즉 감성어휘를 추출하여 사용자의 감성을 측정하는 방법이 가장 보편화되어 있는 방법이다. 본 연구의 선행연구에서는 사용자가 제품을 사용하는 도중에 유발되는 인간의 감성 변화를 나타낼 수 있는 감성어휘들과 대표감성들을 추출하여 제품을 사용하는 도중에 표출되는 사용자의 감성을 측정하기에 적합한 주관적 평가스케일을 도출하였다. 사용자의 감성을 측정하기 위한 심리적 측정방법에는 감성어휘를 이용한 체크리스트 외에도 자기-보고 질문지형 스케일도 널리 사용되고 있다. 따라서 본 연구에서는 선행연구를 통해 도출한 주관적 평가스케일을 보다 더 효과적으로 활용하기 위하여 자기-보고 질문지형 스케일을 제안하였다. 향후 제안한 평가스케일에 대한 신뢰도(reliability) 및 타당도(validity) 검증을 통해 수정 보완함으로써 제품을 사용하면서 자연스럽게 표출되는 사용자의 감성을 효과적으로 측정하기 위한 척도로 활용할 수 있을 것이다.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.140-145
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• 1997

A stuey to investigate the perception characteristics of color and brightness was conducted in a combined PC and TV monitor, The objective of this study is to suggest user's favorite color temperature in PC mode and user's favorite contrast in TV mode. Investigated factors were monitor coating(coatiog vs. non-coation)and screen brightness (30fL vs. 35fL)in first experiment and monitor coating and pucture movement(static vs. dynamic) in second experiment. The first experiment was conducted in TV mode. Twenty-three subjects (male 12, female 11) perticipated in this experiment. In first experiment, average color temperatures were about 8000K in all experimental conditions. In addition, there was significant difference between coating and non-coating screen at 0.1 level. In second experiment, average contrasts were obtained in all esperimental conditions. There was significant difference between coating and ndn-coating screen at 0.05 level, In addition, there was significant difference between static picture and dynamic picture at 0.1 level

• The Journal of the Korea Contents Association
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• v.7 no.8
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• pp.86-93
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• 2007

Online game industry is also making much efforts in developing games that have emotional disposition which is rapidly growing by the increase of emotional demand by the user. In the online game development that induces immersion stimulating the emotion of the human has the evaluation stage it must surely pass, and in this stage, emotional evaluation system is known as the evaluation method that one can verify the function, usage and human emotion desire of the game before its launching. Nevertheless, at this situation the studying result is absent in the verification of efficiency and validity of the emotional evaluation system, this study is to work on the availability and validity of the emotional evaluation system as the evaluation tool of the game comparing with the Jakob Nielsen's evaluation system through common user group which are the subjects.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.197-206
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• 2010

For an emotion retrieval system implementation to support pedestrian navigation, coordinating the pedestrian emotion model with the system user's emotion is considered a key component. This study proposes a new method for capturing the user's model that corresponds to the pedestrian emotion model and examines the validity of the method. In the first phase, a database comprising a set of interior images that represent hypothetical destinations was developed. In the second phase, 10 subjects were recruited and asked to evaluate on navigation and satisfaction toward each interior image in five rounds of navigation experiments. In the last phase, the subjects' feedback data was used for of the pedestrian emotion model, which is called ‘learning' in this study. After evaluations by the subjects, the learning effect was analyzed by the following aspects: recall ratio, precision ratio, retrieval ranking, and satisfaction. Findings of the analysis verify that all four aspects significantly were improved after the learning. This study demonstrates the effectiveness of the learning algorithm for the proposed pedestrian emotion model. Furthermore, this study demonstrates the potential of such pedestrian emotion model to be well applicable in the development of various mobile contents service systems dealing with visual images such as commercial interiors in the future.

• Science of Emotion and Sensibility
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• v.9 no.spc3
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• pp.235-241
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• 2006

This paper predict user acceptance of smart clothing. The present research develops and validates new products for smart clothing. Studies suggest that further analysis of the process be undertaken to better establish properties for smart clothing, underlying structures and stability over innovative technologies. The findings reported in this paper should be useful methods which identify user needs. such findings in now provide a way to explain technology acceptance. Both of qualitative and quantitative methods, were applied to this study in order to find out user needs for smart clothing. We are writing scenarios and conducting both focused group interviews and a survey to assess the user's interest. The purpose of the survey is to evaluate the importance of the functions and to evaluate the degree of the participant's feeling and attitude. Furthermore, we explore the nature and specific influences of factors that may affect the user perception and usage.