• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.197-203
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• 2005

In this paper, we propose an emotion recognition using facial Images to effectively design human interface. Facial database consists of six basic human emotions including happiness, sadness, anger, surprise, fear and dislike which have been known as common emotions regardless of nation and culture. Emotion recognition for the facial images is performed after applying the discrete wavelet. Here, the feature vectors are extracted from the PCA and LDA. Experimental results show that human emotions such as happiness, sadness, and anger has better performance than surprise, fear and dislike. Expecially, Japanese shows lower performance for the dislike emotion. Generally, the recognition rates for Korean have higher values than Japanese cases.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.83-94
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• 2011

Main researching issue in affective computing is to give a machine the ability to recognize the emotion of a person and to react it properly. Efforts in that direction have mainly focused on facial and oral cues to get emotions. Postures have been recently considered as well. This paper aims to discriminate emotions posture by identifying and measuring the saliency of posture features that play a role in affective expression. To do so, affective postures from human subjects are first collected using a motion capture system, then emotional features in posture are described with spatial ones. Through standard statistical techniques, we verified that there is a statistically significant correlation between the emotion intended by the acting subjects, and the emotion perceived by the observers. Discriminant Analysis are used to build affective posture predictive models and to measure the saliency of the proposed set of posture features in discriminating between 6 basic emotional states. The evaluation of proposed features and models are performed using a correlation between actor-observer's postures set. Quantitative experimental results show that proposed set of features discriminates well between emotions, and also that built predictive models perform well.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.573-580
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• 2005

In this paper, we propose an emotion recognition using static and dynamic facial images to effectively design human interface. The proposed method is constructed by HMM(Hidden Markov Model), PCA(Principal Component) and wavelet transform. Facial database consists of six basic human emotions including happiness, sadness, anger, surprise, fear and dislike which have been known as common emotions regardless of nation and culture. Emotion recognition in the static images is performed by using the discrete wavelet. Here, the feature vectors are extracted by using PCA. Emotion recognition in the dynamic images is performed by using the wavelet transform and PCA. And then, those are modeled by the HMM. Finally, we obtained better performance result from merging the recognition results for the static images and dynamic images.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2006.05a
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• pp.125-130
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• 2006

The various kinds of consumption belong to a general category and at the same time the expression of most basic aspiration in the human life. Since the ancient times, the consuming activities have lasted with the other basic activities and the consuming space conducting consumption has developed as physical devices along with the human history. Those companies that have been given attention and getting favorable impression currently being selected by the consumers are now concentrated on the storytelling marketing. The storytelling marketing is that the emotion-oriented marketing activities give consumers the opportunities to enjoy the product contained stories to put the stories to marketing activities. It approaches to consumer with human story emotionally rather than rationally and heart rather than mind. Recently, the architecture has become artistic either it was linked and contacted media or part of marketing. We think that the story telling marketing is the eternal triangle among art, architecture and marketing that is a propensity or movement to interior at this time. I found out that the storytelling marketing methodology is able to touch the consumer's heart and stimulate consumption aspiration that makes new circumstances and experience expressing space. And for that, effective marketing methodology is to give the consumers a more exciting and enjoyable motivation in accord with the modern society to give companies positive image to customers and accordingly for the companies to gain profits. The story telling space that is filled with ideas which produce new circumstance and experience using the established narrative and theme will be required continuously and able to develop in the future.

• Korean Institute of Interior Design Journal
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• v.22 no.4
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• pp.41-51
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• 2013

Lately in many cases, Spaces are designed by stimulating user's sensibility, emotion, psychological software over based on the user behavior and purpose of space. Because space is not only practical using and use purpose but also the place for expressing ourselves by experiences. But space is a physical thing. so we need to arrange a structure of abstract and formless source of design by sophisticated grammaticalization. Especially storytelling of that abstract thing have characteristics of relation, process among users and space. because storytelling is focused on the discourse of stories and relationship record of that discourses. So this is used by expression device for user's emotion things and subjects in numerous cases. And storytelling is the basic, important element for user's experience in a space. By the way, Overlapping is also basic element for being possible to make experiences by concrete thing. that is because, Overlapping is layering phenomenon of some objects. Overlapping is made distance, distance make depth, and this relations take us an experience. Finally storytelling, Overlapping and space of experience are relation of cause and effect. So in this thesis, researcher looks for the relation characteristics between storytelling and overlapping by experience. and makes the abstract source into concrete and sophisticated formular.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.05a
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• pp.219-222
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• 2009

Rapid object recognition is one of the main stream research themes focusing to reveal how human recognizes object and interacts with environment in natural world. This field of study is of consequence in that it is highly important in evolutionary perspective to quickly see the external objects and judge their characteristics to plan future reactions. In this study, we investigated how human detect natural scene objects and categorize them in a limited time frame. We applied Magnetoencepahlogram (MEG) while participants were performing detection (e.g. object vs. texture) or basic-level categorization (e.g. cars vs. dogs) tasks to track the dynamic interaction in human brain for rapid object recognition process. The results revealed that detection and categorization involves different temporal and functional connections that correlated for the successful recognition process as a whole. These results imply that dynamics in the brain are important for our interaction with environment. The implication from this study can be further extended to investigate the effect of subconscious emotional factors on the dynamics of brain interactions during the rapid recognition process.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.121-138
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• 2017

As information users seek multimedia with a wide variety of information needs, information environments for multimedia have been developed drastically. More specifically, as seeking multimedia with emotional access points has been popular, the needs for indexing in terms of abstract concepts including emotions have grown. This study aims to analyze the index terms extracted from Getty Image Bank. Five basic emotion terms, which are sadness, love, horror, happiness, anger, were used when collected the indexing terms. A total 22,675 index terms were used for this study. The data are three sets; entire emotion, positive emotion, and negative emotion. For these three data sets, co-word occurrence matrices were created and visualized in weighted network with PNNC clusters. The entire emotion network demonstrates three clusters and 20 sub-clusters. On the other hand, positive emotion network and negative emotion network show 10 clusters, respectively. The results point out three elements for next generation of multimedia retrieval: (1) the analysis on index terms for emotions shown in people on image, (2) the relationship between connotative term and denotative term and possibility for inferring connotative terms from denotative terms using the relationship, and (3) the significance of thesaurus on connotative term in order to expand related terms or synonyms for better access points.

• Science of Emotion and Sensibility
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• v.14 no.4
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• pp.503-512
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• 2011

Recently in HCI research, emotion recognition is one of the core processes to implement emotional intelligence. There are many studies using bio signals in order to recognize human emotions, but it has been done merely for the basic emotions and very few exists for the other emotions. The purpose of present study is to confirm the difference of autonomic nervous system (ANS) response in three emotions (boredom, pain, and surprise). There were totally 217 of participants (male 96, female 121), we presented audio-visual stimulus to induce boredom and surprise, and pressure by using the sphygmomanometer for pain. During presented emotional stimuli, we measured electrodermal activity (EDA), skin temperature (SKT), electrocardiac activity (ECG) and photoplethysmography (PPG), besides; we required them to classify their present emotion and its intensity according to the emotion assessment scale. As the results of emotional stimulus evaluation, emotional stimulus which we used was shown to mean 92.5% of relevance and 5.43 of efficiency; this inferred that each emotional stimulus caused its own emotion quite effectively. When we analyzed the results of the ANS response which had been measured, we ascertained the significant difference between the baseline and emotional state on skin conductance response, SKT, heart rate, low frequency and blood volume pulse amplitude. In addition, the ANS response caused by each emotion had significant differences among the emotions. These results can probably be able to use to extend the emotion theory and develop the algorithm in recognition of three kinds of emotions (boredom, surprise, and pain) by response measurement indicators and be used to make applications for differentiating various human emotions in computer system.

• Science of Emotion and Sensibility
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• v.15 no.2
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• pp.269-282
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• 2012

Laboratory equipment will continue to be developed and created as long as experiments continue. Up until now, the designs have been focused on the functional role; successfully process the study purpose. However, nowadays, the requirements of providing emotional satisfaction of the design, has increased. Even so, the users are normally limited by specific groups and investments on these designs have been neglected due to small annual production by the small market. Through this study, we have conducted an emotional evaluation on Temperature and Humidity Chamber's (TH Chamber) exterior shape. First of all, we extracted emotional words and placed them in categories that represent these emotions and conducted an emotional evaluation on four typical TH chamber models. They were selected based on its door lock type and control box type. The result showed that the 'fixed type' of control box and the 'handle type' of door lock were most favorable by the users, satisfying the five representative emotions; 'Attractiveness', 'Classiness', 'Comfortableness', 'Pleasant' and 'Satisfaction in Usability'. Particularly, all 4 emotional words in the 'Satisfaction in Usability' category recorded over 3.65. This indicates that Satisfaction in Usability is relatively an important category when expressing laboratory equipment. The result of this research is expected to be used as a basic data to find a way of right approach in laboratory equipment design.