• Agribusiness and Information Management
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• v.7 no.1
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• pp.10-20
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• 2015

This study aims to compare and analyze the differences of emotional responses between two types of e-magazines published - one with cinemagraph images and another with general still images. To conduct this study, a total of nine pages were prepared with different contents according to each theme and samples of e-magazine with a total of nineteen sections of images were exposed to a total of thirty persons of subjects. Fifteen persons were assigned to the experimental group viewing the cinemagraph images, and other fifteen persons were assigned to the control group viewing the general still images. As a result of the experiment, the emotional responses of the experimental group and the control group were significantly different. Twenty-eight items of positive emotional responses out of forty-two items of the emotional responses were more found in the experimental group, and fourteen items of negative emotional responses affected the control group more. In the experimental group where the differences in the mean value and significant differences were found, negative emotional responses were not examined but fourteen positive emotional response items such as Loveliness, Merriness, Freshness, Activeness, Attractiveness, Powerfulness, Heartwarming, Joyfulness, Interesting, Confidence, Excitement, Cheerfulness, Humorousness, and Amazement were found; in the control group, positive emotional responses were not found but three items of negative emotional responses such as Ambiguousness, Stuffiness, and Boredom were found.

• The Research Journal of the Costume Culture
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• v.22 no.3
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• pp.399-410
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• 2014

The purpose of this study was to investigate emotional images and preference of knitwear by tone on tone combination. The subjects were 357 university students in Daejeon and Chungnam province, and the measuring instruments were 6 stimuli manipulated by color and tone combination type of background and pattern in the tone and tone combination, and self-administrated questionnaires consisted of emotional images items, preference items, and subjects' demographics attributions. The data were analyzed by Cronbach's ${\alpha}$, factor analysis, t-test, MANOVA and Duncan's multiple range test, using SPSS program. The results were as follows. First, four factors (attractiveness, conspicuity, mildness, and activity) are emerged on emotional images of knitwear. Second, color had main effects on emotional images and preference. Gray color was perceived as most attractive image and more preferred than others. Third, tone combination type had some effects on emotional images. Vivid tone background/light tone pattern was perceived more attractive image but less conspicuous and mild than light tone background/vivid tone pattern. Forth, subjects' gender had an effects on conspicuous image. Male was perceived more conspicuous image on knitwear stimuli than female. Fifth, color and subjects' gender had interaction effects on attractiveness image and preference. Male perceived that blue is more attractive and preferred than female.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1125-1133
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• 2014

Recently, there are many researches have been studying for analyzing user interests and emotions based on users profiles and diverse information from Social Network Services (SNSs) due to their popularities. However, most of traditional researches are focusing on their researches based on single resource such as text, image, hash tag, and more, in order to obtain what user emotions are. Hence, this paper propose a method for obtaining user emotional information by analyzing texts and images both from Instagram which is one of the well-known image based SNSs. In order to extract emotional information from given images, we firstly apply GRAB-CUT algorithm to retrieve objects from given images. These retrieved objects will be regenerated by their representative colors, and compared with emotional vocabulary table for extracting which vocabularies are the most appropriate for the given images. Afterward, we will extract emotional vocabularies from text information in the comments for the given images, based on frequencies of adjective words. Finally, we will measure WUP similarities between adjective words and emotional words which extracted from the previous step. We believe that it is possible to obtain more precise user emotional information if we analyzed images and texts both time.

• Journal of the Ergonomics Society of Korea
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• v.31 no.3
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• pp.427-435
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• 2012

The aim of this study is to investigate facial temperature changes induced by facial expression and emotional state in order to recognize a persons emotion using facial thermal images. Background: Facial thermal images have two advantages compared to visual images. Firstly, facial temperature measured by thermal camera does not depend on skin color, darkness, and lighting condition. Secondly, facial thermal images are changed not only by facial expression but also emotional state. To our knowledge, there is no study to concurrently investigate these two sources of facial temperature changes. Method: 231 students participated in the experiment. Four kinds of stimuli inducing anger, fear, boredom, and neutral were presented to participants and the facial temperatures were measured by an infrared camera. Each stimulus consisted of baseline and emotion period. Baseline period lasted during 1min and emotion period 1~3min. In the data analysis, the temperature differences between the baseline and emotion state were analyzed. Eyes, mouth, and glabella were selected for facial expression features, and forehead, nose, cheeks were selected for emotional state features. Results: The temperatures of eyes, mouth, glanella, forehead, and nose area were significantly decreased during the emotional experience and the changes were significantly different by the kind of emotion. The result of linear discriminant analysis for emotion recognition showed that the correct classification percentage in four emotions was 62.7% when using both facial expression features and emotional state features. The accuracy was slightly but significantly decreased at 56.7% when using only facial expression features, and the accuracy was 40.2% when using only emotional state features. Conclusion: Facial expression features are essential in emotion recognition, but emotion state features are also important to classify the emotion. Application: The results of this study can be applied to human-computer interaction system in the work places or the automobiles.

• Journal of the Korean Society of Costume
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• v.66 no.2
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• pp.15-31
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• 2016

Flower images are used as a design motif in various fields. Flower printings in clothes, in particular, usually represent nature. This study sets out to identify the characteristics of different fashion styles with flower printings, as well as the preferences and emotional images of Korean women in their 20s. The flower printings used in fashion design were classified into 5 types of styles: Modern, Natural Romantic, Maximalism, Neo-Hippie, and Ethnic style. Literature review and survey were conducted to identify the emotional images associated with the flower printings, as well as women's preferences. Through literature review, this study noted the formative elements of flower printings and their characteristics, as expressed in fashion designs. Then, the different styles were classified in order to provide theoretical foundation for the survey. The results of the study were significant in that they contributed to the definition and academic systemization of the characteristics of fashion styles with flower printings. Moreover, the study opened up possibilities for utilizing flowers to express a greater variety of meanings and influences in fashion. The findings can be used to enable fashion styles and emotional influences to be expressed through designs using natural motifs besides flowers.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.3_4
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• pp.343-353
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• 2003

In this research, the fashion images, which expressed the same theme during the same season in four different fashion collections, were interpreted as emotional characteristics stemming from different factors according to the emotions and images of the regions where the collections were held. The theme, futurism appeared to be hackneyed and oppressive in Paris fashion which emphasized artistic representation of the theme. And futurism appeared to be expressed to be dazzling, unnatural in London fashion which was innovative and avant-garde. And the New York fashion, which accentuated practical, sportive, and elegant styles created active and graceful image about the futurism and the Milan fashion showed the balanced mixture of the three cities' images above. It is interpreted that our domestic fashion consumers think artistic, formative, original, and emotional images as hackneyed and oppressive. On the other hand, they feel comfortable, cheerful, unaffected and graceful about the images that are functional (rather than artistic), sportive, and moderately elegant. And the innovative and avant-garde images like the ones in London collection seem to make people feel unnatural, dazzled, and even depressed. In short, domestic fashion consumers think that the excessive, innovative, original, and formative fashion images appeared I London and Paris are hackneyed and dark rather than artistic, original, or dynamic. On the contrary, the moderate, practical, sportive and elegant New York images and the Milan's which equally showed the three cities' characteristics are regarded as comfortable, elegant, bright, and positive. This result indicates that the fashion market in certain regions seek shared fashion trends and the difference between the regions reflects the different interpretation of fashion themes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1464-1485
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• 2021

Emotional style of multimedia art works are abstract content information. This study aims to explore emotional style transfer method and find the possible way of matching music with appropriate images in respect to emotional style. DCNNs (Deep Convolutional Neural Networks) can capture style and provide emotional style transfer iterative solution for affective image generation. Here, we learn the image emotion features via DCNNs and map the affective style on the other images. We set image emotion feature as the style target in this style transfer problem, and held experiments to handle affective image generation of eight emotion categories, including dignified, dreaming, sad, vigorous, soothing, exciting, joyous, and graceful. A user study was conducted to test the synesthesia emotional image style transfer result with ground truth user perception triggered by the music-image pairs' stimuli. The transferred affective image result for music-image emotional synesthesia perception was proved effective according to user study result.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.1-10
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• 2024

While technologies such as the 4th revolution and artificial intelligence (AI), which create new value through the convergence of intelligent information technology, are becoming hot topics, the beauty industry is rapidly developing and combining information and communication technology to produce beauty items based on smartphones among mobile technologies. As the area of expands, YouTube is forming a network through various means of information. In particular, beauty-related YouTube videos are a field of great interest and popularity among the public. By classifying the makeup characteristics according to the emotional images shown in domestic YouTube videos by emotional image and identifying the characteristics of makeup, the needs for watching YouTube makeup videos are identified. We aim to build trust in the delivery of information about makeup. The emotional images were divided into four types: 'modern', 'natural', 'gorgeous', and cute. Among the domestic makeup YouTubers, Pony, Isabe and Shinnim, Lamuque were selected. By organizing more diverse makeup-related content systematically and creatively, we expect to have a positive influence on k-makeup not only domestically but also overseas. We aim to provide basic data for follow-up research on makeup YouTuber videos in the field of cosmetology and contribute to marketing plans for the development of the beauty content industry and establishment of promotional strategies.

• Korean Institute of Interior Design Journal
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• v.22 no.5
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• pp.171-178
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• 2013

In this study, we sought to find out the effect of different emotional interior images of the community facilities in an apartment complex on a youth brain wave by analyzing an Electroencephalograph (EEG). Based on the frequency of usage, we selected learning facilities, cultural facilities, and sport facilities. For brain stimulation, the visual stimulants with three different emotional words, cheerful, gentle, and elegant, were used based on I.R.I image scale. Overall, total nine different emotional images were used. Based on our findings, we conclude that: first, in order to improve learning concentration of the youth, a learning facility for the youth needs to be designed by skillfully combining the soft and comfortable colors from the gentle image and the murky and dark colors from the elegant image. Second, when designing a cultural facility, it is preferable to consider the elegant image for a calm and comfortable space. Third, a sport facility design needs to preclude dark colors and apply light colors to create a dynamic and lively space. Furthermore, we found out that the youth has established static images of each functionally different facility through their experience and learning. Therefore, it is imperative to plan community facilities in an apartment complex in a way to connect the space function with the emotional characteristics of the youth in order to support and encourage energetic activities and learning of the community youth.

• Korean Institute of Interior Design Journal
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• v.20 no.6
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• pp.71-78
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• 2011

Although the recognition and emotion about space is subjective and individual, if standard is proposed through common factor, objective, quantified space image evaluation will be available. In addition, space image evaluation standard caused by recognitive-emotional factor can meet requests of space users and increase psychological satisfactions. The purpose of this study is to grasp the space image caused by recognitive-emotional factor in space with PAD model and analyze the evaluation of space image giving visual, recognitive and emotional effects. The analysis result revealed that 'joyfulness' and access-avoidance had a very similar distribution. The result means that space is evaluated with the degree of 'joyfulness' for space and it is led by approach-avoidance behavior. The recognition factor that forms and evaluates space image and decides approach-avoidance is expressed as adjective images such as 'fresh, joyful, light and static and its emotional factors are adjective images such as 'calm, allowable, joyful and quiet'.