• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.6
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• pp.949-964
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• 2021

Accumulation of high-quality data is crucial for AI learning. The goal of using AI in fashion service is to propose of a creative, personalized solution that is close to the know-how of a human operator. These customized solutions require an understanding of fashion products and emotions. Therefore, it is necessary to accumulate data on the attributes of fashion products and fashion emotion. The first step for accumulating fashion data is to standardize the attribute with coherent system. The purpose of this study is to propose a fashion emotional classification system. For this, images of fashion products were collected, and metadata was obtained by allowing consumers to describe their emotions about fashion images freely. An emotional classification system with a hierarchical structure, was then constructed by performing frequency and CONCOR analyses on metadata. A final classification system was proposed by supplementing attribute values with reference to findings from previous studies and SNS data.

• 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 the Korean Society of Clothing and Textiles
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• v.25 no.5
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• pp.833-844
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• 2001

The purposes of this study were 1) to identify the effects of store image and stores entertainment environment image on attitude toward store and store patronage intention through emotions toward store, and 2) to identify the effects of sensation-seeking tendency, hedonic shopping orientation and shopping motives on store image, stores entertainment environment image, attitude toward store and store patronage intention. The data were collected from 416 female adolescents who visited stores located in Dongdaemoon, Seoul, via self-administered questionnaires, and were analyzed by frequency, factor analysis, multiple regression and path analysis. The results of this study were as follows : (1) According to path analysis, store image and stores entertainment environment image affected emotions toward store and attitude toward store, and affected store patronage intention through a mediator, emotions toward store. (2) Among the factors related to store images, stores entertainment environment image had the greatest effect on store patronage intention. (3) Sensation-seeking tendency, hudonic shopping orientation and shopping motives affected store image, stores entertainment environment image, emotions toward store and attitude toward store directly and indirectly through store image and stores entertainment environment image. (4) The most significant factor in explaining all these relations was hedonic shopping orientation.

• Smart Media Journal
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• v.12 no.9
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• pp.81-88
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• 2023

Recently, communication through online is increasing due to the spread of non-face-to-face services due to COVID-19. In non-face-to-face situations, the other person's opinions and emotions are recognized through modalities such as text, speech, and images. Currently, research on multimodal emotion recognition that combines various modalities is actively underway. Among them, emotion recognition using speech data is attracting attention as a means of understanding emotions through sound and language information, but most of the time, emotions are recognized using a single speech feature value. However, because a variety of emotions exist in a complex manner in a conversation, a method for recognizing multiple emotions is needed. Therefore, in this paper, we propose a multi-emotion regression model that extracts feature vectors after preprocessing speech data to recognize complex, inherent emotions and takes into account the passage of time.

• 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.

• Journal of the Korean Society of Costume
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• v.23
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• pp.53-65
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• 1994

The images signifying flight in modern costumes are not made of one characteristic but the combination of complex meanings. Among the distinctive features some of them are as follows. First, the flying styles found in the costumes showed the birds as agents which sent human spirit to the celestial body. By simplifying the images of the wings connecting the present age with the heavenly body, the transforming emotions towards rhythm, direction, and organic curves transcending the real objectively constitutes a new space for expression. Second, colors appeal directly to man's emotions and incites emotional responses. The flying was shown in lines and colors. By using horizontal , vertical, oblique, and spiral lines and contrasted and paralleled colors, man's desire to fly dwells in newly colored space by reflecting speculative emotion through uniting surface. Third, the flying except for the costumes can be found in the advertisement through model's pose and camera technique, the flying itself is described through model's pose, the materials of the costumes, details, and sustaining stuffs. This symbolizes man's wish towards the unknown world vividly and dynamically. As discussed above the spirit of flying was, when expressed distinctively , in accordance with the varying cultural traits and transitions. The shape made by the vitality of symbolizing flying birds and animals along with the flying in the natural aspects such as wind and cloud were reappeared, simplified and symbolized , in modern costumes as consituting a new modeling space.

• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.637-644
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• 2008

Human emotion has been tried to be recognized by physiological measurements in developing emotion machine enabling to understand and react to user's emotion. This study is to find the time-dependent physiological measurements and their variation characteristics for discriminating emotions according to dimensional emotion model. Ten university students were asked to watch sixteen prepared images to evoke different emotions. Their subjective emotions and autonomic nervous responses such as ECG (electrocardiogram), PPG (photoplethysmogram), GSR (Galvanic skin response), RSP (respiration), and SKT(skin temperature) were measured during experiment. And these responses were analyzed into HR(Heart Rate), Respiration Rate, GSR amplitude average, SKT amplitude average, PPG amplitude, and PTT(Pulse Transition Time). TDPs(Time dependent parameters) defined as the delay, the activation, the half recovery and the full recovery of respective physiological signal in this study have been determined and statistically compared between variations from different emotions. The significant tendencies in TDP were shown between emotions. Therefore, TDP may provide useful measurements with emotion recognition.

• Science of Emotion and Sensibility
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• v.14 no.3
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• pp.403-414
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• 2011

The current study examined brain regions associated with aesthetic experience to fractal images using functional MRI. The aesthetic estimations of the images showed that there is a general consensus regarding the perception of beautiful images. Out of 270 fractal images, fifty images rated highest(beautiful images) and fifty images rated lowest(non-beautiful images) were selected and presented to the participants. The two conditions were presented using the block design. Frontal lobes, cingulate gyri, and insula, the areas related to the cognitive and emotional processing in aesthetic experience, were activated when beautiful images were presented. In contrast, the middle occipital gyri and precuneus, the areas associated with experience of negative emotions, were activated when non-beautiful images were presented. The conjunction analysis showed activations in temporal areas in response to beautiful images and activations in parietal areas in response to non-beautiful images. These results indicate that beautiful images elicit semantic interpretations whereas non-beautiful images facilitate abstract processes.

• Science of Emotion and Sensibility
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• v.19 no.3
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• pp.51-58
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• 2016

This study examined the difference between the deaf and hearing adolescents of experiencing emotions and the intensity levels of expressing them. Three different video clips were used to induce pleasure, anger, and sadness. While watching the clips, facial expressions of the participants were recorded. The experienced emotions were measured by a self-report method, and the third person rated participants' expressed emotions based upon the recorded facial images. Two groups (deaf and hearing) were compared if those two groups shared the same experienced emotions, and whether the ratings scored by the third person corresponded with the self-rated scores. There was no significant difference in experienced emotion and its intensity level. However, hearing adolescents showed more intensive responses of pleasure than they reported, while deaf adolescents showed less intensive expressions of happiness than they reported themselves. Thus, hearing people might not be able to detect and fully comprehend how the deaf feel in general circumstances. This further indicates that the deaf adolescents cannot get enough supports from the hearing people when they express their feelings, and consequently, have a possibility of causing misunderstandings, conflicts, or even a break in relationships.

• Science of Emotion and Sensibility
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• v.10 no.1
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• pp.113-125
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• 2007

The aim of the experimental studies described in this paper is to investigate the effects of the face/eye/mouth areas using dynamic facial expressions and static facial expressions on emotional recognition. Using seven-seconds-displays, experiment 1 for basic emotions and experiment 2 for complex emotions are executed. The results of two experiments supported that the effects of dynamic facial expressions are higher than static one on emotional recognition and indicated the higher emotional recognition effects of eye area on dynamic images than mouth area. These results suggest that dynamic properties should be considered in emotional study with facial expressions for not only basic emotions but also complex emotions. However, we should consider the properties of emotion because each emotion did not show the effects of dynamic image equally. Furthermore, this study let us know which facial area shows emotional states more correctly is according to the feature emotion.