• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.123-125
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• 2004

Recently, we are getting to interest in a user friendly machine. The emotion is one of most important conditions to be familiar with people. The machine uses sound or image to express or recognize the emotion. This paper deals with the method of recognizing emotion from the sound. The most important emotional component of sound is a tone. Also, the inference ability of a brain takes part in the emotion recognition. This paper finds empirically the emotional components from the speech and experiment on the emotion recognition. This paper also proposes the recognition method using these emotional components and the transition probability.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.209-218
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• 2013

Early researches in human action recognition have focused on tracking and classifying articulated body motions. Such methods required accurate segmentation of body parts, which is a sticky task, particularly under realistic imaging conditions. Recent trends of work have become popular towards the use of more and low-level appearance features such as spatio-temporal interest points. Given the great progress in pose estimation over the past few years, redefined views about pose-based approach are needed. This paper addresses the issues of whether it is sufficient to train a classifier only on low-level appearance features in appearance approach and proposes effective pose-based approach with pose estimation for emotional action recognition. In order for these questions to be solved, we compare the performance of pose-based, appearance-based and its combination-based features respectively with respect to scenario of various emotional action recognition. The experiment results show that pose-based features outperform low-level appearance-based approach of features, even when heavily spoiled by noise, suggesting that pose-based approach with pose estimation is beneficial for the emotional action recognition.

• Korean Institute of Interior Design Journal
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• v.22 no.6
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• pp.119-129
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• 2013

For commercial inner space, studies about brand communication and VMD to inform brand identity to customers are very important. Accordingly, the study conducted questionnaire survey about 'emotional reaction, brand recognition, brand communication and satisfaction on VMD expressional elements' of customers and brand-related personnel on the ZARA flagship store. Through analysis of difference of evaluation on surveyed items between customers and brand personnels, importance of direction of VMD design applying brand communication which can satisfy customers and application of brand communication was verified. Specific results of the research are as follows: First, comparing brand personnel's expectation of recognition of their brand from customers, substantial level of recognition of brand by customers was lower. It is necessary for improvement through consumer analysis in order to raise brand recognition. Second, as the result of analysis of emotional reaction on VMD, it needs to lead customers to positive emotional reaction close to the brand plan intention by inducing 'exciting and sensational' brand concept to emotional reactions through comprehensive VMD image management and leading to 'free and convenient' emotional reaction and then communications with customers and minimizing emotional differences. Third, for brand communication and creation of 'interest', intention of ZARA, it needs to get maximum communicative effects with 'young' VMD design. Fourth, for satisfaction survey on VMD expressional elements, customers was less satisfied than brand personnel. Accordingly, in order to raise customers' satisfaction, show windows, entry, mannequins and objets should be planned with priority and it should also satisfy customers through communications with customers including advertisement and marketing.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.381-391
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• 2018

The goal of current study was to investigate the perception of emotional lighting according to the types of exercise participation of fitness center users. The subjects of this study were 292 people in Gyeongin area fitness center. As a survey tool, the color types used in the study of Oh & Kwak(2015) were used, and the color recognition was based on the emotional adjective scale used in Lee(1997). Data were analyzed using crossover, independent t-test and one-way ANOVA using SPSS23.0. The following conclusions can be drawn from the results of this study. First, emotional lighting color preference of fitness users varies according to Gender. Second, the difference of perception of color by emotional illumination of fitness users was found to be partially different in color and sex. Third, there was a difference in color recognition among emotional lighting color recognition according to exercise participation type of fitness users.

• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.476-488
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• 2017

The object of this study was to survey the relationship between emotional self-support and the level of subjective health recognition of participators in the self support program. The health condition which is recognized subjectively by participators could affect the participation motive and the attitude to the program, and could be connected to the achievement of self-support. Therefore I tried to survey the implications and the relationship between emotional self-support and the level of subjective health recognition in terms of progress for the economic self-support. The objectives were self-support program participators in Wonju, and 127 questionaries were collected. The results of this study were as followings; First, there was the positive relationship between emotional self-support and the level of subjective health recognition. Second, the participation period in the self-support program affected emotional self-support and the level of subjective health recognition negatively, and the affects of the ages were meaningless. The suggestion of this study is that the level of emotional self-support and subjective health recognition could be developed if the emotional and psychological program is developed which makes the conditional pensioners perceive the living attitude and the thoughts to the works positively.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.271-279
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• 2012

Objective: This study classified three different emotional states(boredom, pain, and surprise) using physiological signals. Background: Emotion recognition studies have tried to recognize human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 122 college students participated in this experiment. Three different emotional stimuli were presented to participants and physiological signals, i.e., EDA(Electrodermal Activity), SKT(Skin Temperature), PPG(Photoplethysmogram), and ECG (Electrocardiogram) were measured for 1 minute as baseline and for 1~1.5 minutes during emotional state. The obtained signals were analyzed for 30 seconds from the baseline and the emotional state and 27 features were extracted from these signals. Statistical analysis for emotion classification were done by DFA(discriminant function analysis) (SPSS 15.0) by using the difference values subtracting baseline values from the emotional state. Results: The result showed that physiological responses during emotional states were significantly differed as compared to during baseline. Also, an accuracy rate of emotion classification was 84.7%. Conclusion: Our study have identified that emotions were classified by various physiological signals. However, future study is needed to obtain additional signals from other modalities such as facial expression, face temperature, or voice to improve classification rate and to examine the stability and reliability of this result compare with accuracy of emotion classification using other algorithms. Application: This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals as well as is able to be applied on human-computer interaction system for emotion recognition. Also, it can be useful in developing an emotion theory, or profiling emotion-specific physiological responses as well as establishing the basis for emotion recognition system in human-computer interaction.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.935-939
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• 2003

The emotion recognition is one of the most significant interface technologies which make the high level of human-machine communication possible. The central nervous system stimulated by emotional stimuli affects the autonomous nervous system like a heart, blood vessel, endocrine organs, and so on. Therefore bio-signals like HRV, ECG and EEG can reflect one' emotional state. This study investigates the correlation between emotional states and bio-signals to realize the emotion recognition. This study also covers classification of human emotional states, selection of the effective bio-signal and signal processing. The experimental results presented in this paper show possibility of the emotion recognition.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.1-9
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• 2015

Emotion recognition and regular controls are concentrated interest in computer studies to emotional changes. Thus, the quantified by objective assessment methods are essential for application of color sensibility computing situations. In this paper, it is applied to a digital color image emotion emotional computing calculations numbered recognized as one representation. Emotional computing research approach consists of a color attribute to the image recognition focused sensibility and emotional attributes of color is the color, brightness and saturation separated by. Computes the sensitivity weighted according to the score and the percentage increase or decrease in the sensitivity property tone applied to emotional expression. Sensitivity calculation is free-degree (X), and calculates the tension (Y-axis). And free-level (X-axis) coordinate of emotion, which is located the intersection of the tension (Y-axis) as a sensitivity point. The emotional effect of the Russell coordinates are utilizing the core (Core Affect). Tue numbers represent the size and sensitivity in the emotional relationship between emotional point location and quantified by computing the color sensibility.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.613-617
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• 2021

According to the growth of the service industry, stresses from emotional labor workers have been emerging as a social problem, thereby so-called the Emotional Labor Protection Act was implemented in 2018. However, insufficient substantial protection systems for emotional workers emphasizes the necessity of a digital stress management system. Thus, in this paper, we suggest a stress detection system for customer service representatives based on deep learning facial expression recognition. This system consists of a real-time face detection module, an emotion classification FER module that deep-learned big data including Korean emotion images, and a monitoring module that only visualizes stress levels. We designed the system to aim to monitor stress and prevent mental illness in emotional workers.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.33-43
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• 2023

Not only emotions affect physical sensations, but they also have an impact on physical movements. The responses to emotions vary depending on the type of emotional stimuli. However, research on the effects of emotional stimuli on the activation of bodily movements has not been rigorously examined, and these effects have not been investigated in Autonomous Emotion Recognition (AER) systems. In this study, we aimed to compare the emotional responses of 20 participants to three types of emotional stimuli (words, pictures, and videos) and investigate their activation or deactivation for the AER system. Our dependent measures included emotional responses, computer-based self-reporting methods, and bodily movements recorded using motion capture devices. The results suggested that video stimuli elicited higher levels of emotional movement, and emotional movement patterns were similar across different types of emotional stimuli for happiness, sadness, anger, and neutrality. Additionally, the findings indicated that bodily changes observed during video stimuli had the highest classification accuracy. These findings have implications for future research on the bodily changes elicited by emotional stimuli.