• Journal of the Korean Society for Precision Engineering
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• v.23 no.5 s.182
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• pp.68-76
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• 2006

The ability to recognize human emotion is one of the hallmarks of human-robot interaction. Hence this paper describes the realization of emotion recognition. For emotion recognition from voice, we propose a new feature called frequency range of meaningful signal. With this feature, we reached average recognition rate of 76% in speaker-dependent. From the experimental results, we confirm the usefulness of the proposed feature. We also define the noise environment and conduct the noise-environment test. In contrast to other features, the proposed feature is robust in a noise-environment.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.282-288
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• 2000

This paper describes the basic concept and processes underlying human design technology, and outlines Kansei design base on this logical approach.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2012.05a
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• pp.28-29
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• 2012

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.4
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• pp.364-371
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• 2013

Emotion Recognition is one of the important part to develop in human-human and human computer interaction. In this paper, we have focused on the performance of multi-class SVM (Support Vector Machine) with Gaussian RFB (Radial Basis function) kernel, which has been used to solve the problem of emotion recognition from physiological signals and to improve the accuracy of emotion recognition. The experimental paradigm for data acquisition, visual-stimuli of IAPS (International Affective Picture System) are used to induce emotional states, such as fear, disgust, joy, and neutral for each subject. The raw signals of acquisited data are splitted in the trial from each session to pre-process the data. The mean value and standard deviation are employed to extract the data for feature extraction and preparing in the next step of classification. The experimental results are proving that the proposed approach of multi-class SVM with Gaussian RBF kernel with OVO (One-Versus-One) method provided the successful performance, accuracies of classification, which has been performed over these four emotions.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.683-688
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• 2008

The emotional information processing is to simulate and recognize human sensibility, sensuality or emotion, to realize natural and harmonious human-machine interface. This paper proposes an emotion-based image retrieval method. In this method, user can choose a linguistic query among some emotional adjectives. Then the system shows some corresponding representative images that are pre-evaluated by experts. Again the user can select a representative one among the representative images to initiate traditional content-based image retrieval (CBIR). By this proposed method any CBIR can be easily expanded as emotion-based image retrieval. In CBIR of our system, we use several color and texture visual descriptors recommended by MPEG-7. We also propose a fuzzy similarity measure based on Choquet integral in the CBIR system. For the communication between system and user, a relevance feedback mechanism is used to represent human subjectivity in image retrieval. This can improve the performance of image retrieval, and also satisfy the user's individual preference.

• Science of Emotion and Sensibility
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• v.20 no.4
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• pp.79-88
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• 2017

As the age in which the importance of sensitivity has increased, education for the future generation regarding emotion engineering, affective recognition and cognitive science have taken center stage. We measure human's emotion quantitatively, analyze evaluation and apply them to various services in life, which are based on human technology. Therefore, we need the education which is related to emotion science to cultivate talented people. The goal of this paper is to suggest the possibility of emotion science education and effective methods through development of the STEAM (Science, Technology, Engineering, Arts, Mathematics) program which can teach emotion science to early elementary school students by applying it to pilot classes. For this study, first, we build a program, 'The mind made by figure' for student of early elementary school. The method of STEAM was used in this program, because it is an effective system to educate the emotion science. We recognize the needs and value of this program development through theory and benchmarking of STEAM related to emotion science. And then the contents of class, activities, course book and kit are designed with elementary school textbook of pertinent grade. Secondly, we analyze the result which is applied in two pilot classes of second grade by satisfaction survey and teacher interview. As a result, the average of satisfaction level was very high (4.40/5), Class participation was especially high. Third, we discuss the ability, value and limits of this program based on the result of analysis. The outcome of this research shows that students of early elementary school who have difficulty in understanding science can approach the education program related to emotion science with ease and interest. We hope this education will help students understand emotion science effectively, and to train people to lead the emotion centered era.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.277-281
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• 2000

This paper deals with the construction of database system for the human sensibility evaluation.Recently, although a great deal of research efforts have been made to find out the relationships between products and emotion, the main focus of studies have been on visual and auditory sense and less on human sensibility evaluation. Therefore, we think that continuous and systematic studies on odors and the construction of database system are strongly needed in order to enhance the competitive power of products related to them.In this paper, we developed a human sensibility evaluation database system fitted with the characteristics of our country. 쏜 design procedures of database system are presented. According to these procudures, a new database system is implemented on personal computer using MS Access and Visual and is validated.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1999.03a
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• pp.195-199
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• 1999

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.138-145
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• 2008

The development of human-friendly game technologies understanding and responding to human emotion is a very crucial element in designing games. Out of emotion derived from games, this study attempted to define characteristics of games as a meaning representing the degree of reaching the targeted emotion. When examining most of researches regarding emotion, it has been noted that they tried to extract the most representative emotion through the systematization of emotional vocabulary and evaluate it by the association with the design elements in question. However, this definition would be beneficial only to understanding the direction of game entity and it could not express the emotion of concrete and objective players. Therefore, this study attempted to analyze the sense correlation of adjectives so as for emotional expressions to be represented accurately corresponding to players' intention, by using adjective thesaurus for the systematic understanding of such game entity.