• Journal of Information Processing Systems
• /
• v.17 no.6
• /
• pp.1138-1156
• /
• 2021

Emotional semantics are the highest level of semantics that can be extracted from an image. Constructing a system that can automatically recognize the emotional semantics from images will be significant for marketing, smart healthcare, and deep human-computer interaction. To understand the direction of image emotion recognition as well as the general research methods, we summarize the current development trends and shed light on potential future research. The primary contributions of this paper are as follows. We investigate the color, texture, shape and contour features used for emotional semantics extraction. We establish two models that map images into emotional space and introduce in detail the various processes in the image emotional semantic recognition framework. We also discuss important datasets and useful applications in the field such as garment image and image retrieval. We conclude with a brief discussion about future research trends.

• Science of Emotion and Sensibility
• /
• v.17 no.2
• /
• pp.45-54
• /
• 2014

In recent years, advancing technology and growing interest in neuromarketing and neurobranding have led to foundational research that facilitates a better understanding of consumers' affective responses and unconscious information processing. However, the areas of aesthetics and design have remained largely unaffected by such advances and implications. The purpose of this study is to present a systematic review of the neuroscientific evidence aimed at sensible design for design and marketing researchers interested in exploring neuroaesthetics, an interdisciplinary area by nature. Sciencedirect, EBSCO, and the Google Scholar database were searched in February 2014 to select and review previous studies of aesthetics involving neuroscience. Twenty-eight studies were reviewed and divided into two categories: reward system and emotion. In addition to discussions on previous approaches, future research directions focusing on the process of aesthetic judgments (e.g., design elements, marketing stimuli) are proposed.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.15 no.3
• /
• pp.159-165
• /
• 2015

The need for the recognition of music emotion has become apparent in many music information retrieval applications. In addition to the large pool of techniques that have already been developed in machine learning and data mining, various emerging applications have led to a wealth of newly proposed techniques. In the music information retrieval community, many studies and applications have concentrated on tag-based music recommendation. The limitation of music emotion tags is the ambiguity caused by a single music tag covering too many subcategories. To overcome this, multiple tags can be used simultaneously to specify music clips more precisely. In this paper, we propose a novel technique to rank the proper tag combinations based on the acoustic similarity of music clips.

• Journal of the Ergonomics Society of Korea
• /
• v.15 no.2
• /
• pp.185-192
• /
• 1996

EEG(electroencephalogram) is characterized with auditory emotion in this study. Twenty university students participated in this study. The auditory stimulus was the natural sounds such as creek sound, clash, machining noise, and etc. They can cause the positive and negative emotion. EEG characteristics according to positive and negative auditory stimuli is tried to observe statistic difference. The significant difference is shown depending on the localized area. The auditory paraameters of EEG variation is examined for defining human emotion qualitatively. The results shows that the alpha and the beta at temproal area may be thd determinat of human auditory emotion.

• Journal of The Korean Association For Science Education
• /
• v.40 no.5
• /
• pp.503-514
• /
• 2020

In a sense that achievement emotion is directly associated with achievement activity of students and its result, drastic changes in educational environment such as expansion of e-learning due to COVID-19 may have a large impact on the achievement emotion of students inevitably. However, studies on the foregoing still remain insufficient, and development of a questionnaire capable of making a quantitative measurement on the achievement emotion of students under the environment of e-learning may become the basis of relevant studies, so this study developed the e-learning Achievement Emotions Questionnaire-Korean Middle school Science(e-AEQ-KMS) and verified its validity. e-AEQ-KMS in this study was developed based on the Achievement Emotions Questionnaire-Korean Middle school Science (AEQ-KMS) and by reflecting characteristics of e-learning science class. With 226 questions in total, the questionnaire is composed to measure 9 kinds of achievement emotion such as enjoyment, hope, pride, relief, anger, anxiety, hopelessness, shame, and boredom under 3 academic situations of class situation, learning situation and testing situation. The result of this study has a great significance in the way that it set out a framework for making a comparative analysis quantitatively on the achievement emotion of Korean middle school students in science for e-learning classes.

• Science of Emotion and Sensibility
• /
• v.1 no.1
• /
• pp.19-24
• /
• 1998

감성과학의 성립요건을 검토하기 위하여 심리학적인 측면에서 감성의 개념정의, 구성개념과 기저 차원, 측정문제를 고찰해 보았다. 감성은 심리학에서는 아직 잘 정제되어 있지 않은 개념으로서 그것을 과학적으로 접근하기 위해서는 조작적으로 정의가능한 구성 개념들로 분해될 수 있어야 한다는 것이 논의되었다. 감성의 측정에 대해서는 정서의 측정 방법들이 그대로 적용할 수 있다는 가정 하에 다양한 측정 기법들을 소개하였다.

• Science of Emotion and Sensibility
• /
• v.15 no.1
• /
• pp.133-140
• /
• 2012

We designed a novel individualization process for improving personal emotion recognitions in real time. The designed individualization process was performed by a neutralization algorithm of physiological signals, a subjective emotion reflection of a user updated by personal emotion rules in real time. The physiological signals such as PPG(Photoplethysmography), GSR(Galvanic skin reflex), and SKT(Skin temperature) were measured and analyzed to estimate an emotion states of users. Regulating the emotion status using by emotion rules was performed by reflecting subjective evaluations. The agreement of emotion recognition between of individualization and non-individualization method was estimated by 10 undergraduates (5 females, mean age: $22.1{\pm}2.2$) of Sangmyung University. During the emotion recognition test, 45 images were randomly presented to each participant five times. In results, the proposed individualization process showed the agreement of 71.67 % which was five times higher than when the process was not applied. Therefore, in this study, we demonstrated that the individualization process was significantly useful for customizing emotion recognitions of personal users in real time. The individualization process will be able to improve satisfactions in various emotion related applications and services in the nearer future.

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2001.10a
• /
• pp.59.2-59
• /
• 2001

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2002.11b
• /
• pp.86-87
• /
• 2002

• Science of Emotion and Sensibility
• /
• v.14 no.4
• /
• pp.483-494
• /
• 2011

This paper purposes to develop an artificial emotion reflecting emotional features contains situations, time, and characteristics, also to develop an interactive character having this artificial emotion with a smart phone. The artificial emotion has an Emotion Module and Drive Module for expressing emotion according to external emotional stimulus and internal drive. The Emotion Module administrates emotions according to time, characteristic, interrelation between different emotions. The Drive Module controls sensitivities of emotion according to changing drives over long time. Also due to defence mechanism for expressing emotions, emotions are processed by two pathways: The first pathway which is affected by the Emotion Module and the Drive Module, and the second pathway that is not to be done. We developed an interactive character having the artificial emotion with this structure using smart phone. And we simulated the artificial emotion what differences there are according to situations, characteristic, and time under same input conditions. The result of this paper has meanings developing the interactive character having the artificial emotion actually, and making it possible to personalize an artificial emotion with expressing the artificial emotion using smart phone.