• 조명전기설비학회논문지
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• 제25권10호
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• pp.1-13
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• 2011

The aim of this study is to analyze the emotion adjectives for light emitting diode(LED) light colors using a twofold adjective image scales from Kobayashi and I.R.I. A set of psychophysical experiments using category judgment was conducted in an LED light color simulation system, in order to evaluate each emotion scale coordinate for those test light colors in both adjective image scales. In total, 49 test light colors from a combination of 6 color series were assessed by 15 human observers. As a result, Kobayashi adjective image scale clearly expressed to emotion adjectives of 'Dynamic', 'Casual', 'Chic', 'Cool-casual', 'Modern', and 'Natural' for different hues. In contrast, I.R.I adjective image scale expressed only 2 adjectives of 'dynamic' and 'luxurious' for the all hues.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2007년도 춘계학술대회 및 국제감성 심포지엄
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• pp.27-30
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• 2007

With lots of portable convergence mobile device coming out into the market, companies are now facing to take up consumers' needs. The products are popularized by 'skin function' in the field of hardware, whereas software wise, it's still a long way to follow up the needs. It's been hypothetically known that the Image of Sensitivity Adjective chosen by the users can increase the brand image and value creating capabilities through visualization. We collect the 'adjective' of images of recent products first and on that base, we sort out the most popular 'adjective' through grouping, then we actualize the image with that sample collective body. Then through analyses of the image, we find how they are correlated and what their elements are with the result.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 1997년도 한국감성과학회 연차학술대회논문집
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• pp.220-223
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• 1997

The International Affective Picture System (IAPS) developed by Lang and colleagues[1] is widely used in studies relating a variety of physiological indices to subjective emotions. In this study we investigated whether the IAPS can be used for Koreans without significant cultural biases in their subjective emotional reactions. Thirty IAPS picture slides were presented to a group of 52 college students and different 30 slides with similar 3 dimensional emotion ratings to another group of 42 students. Fof each slieds with exposal time of 8sec, subjects were asked to rate on the Semantic Differential Scale (SDS) and Self-Assessment Manikin (SAM) in the 3 dimensions of pleasure valence, arousal, and domensions of pleasure valence, arousal, and dominance. Fnctor analysis was done for SDS ratings, and correlations of SDS and SAM were calculated. Eighteen bipolar adjective were grouped into 3 dimensions of pleasure, arousal, dominance showing good agreement with previous study. SAM were calculated. Eighteen bipolar adjectives were grouped into 3 dimensions of pleasure, arousal, dominance showing good agreement with the previous study. SAM ratings were highly corrlated with two of the 6 SDS adjective pairs associated with the pleasure and dominance dimensions, but not with those associated with arousal dimension suggerting some cultural differences.

• 한국실내디자인학회논문집
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• 제20권6호
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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'.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 1999년도 춘계학술발표논문집 논문집
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• pp.39-44
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• 1999

The purpose of this study was to extract emotional dimensions from Korean adjectives relating to apartment noise. Noise-related 296 Korean adjectives were extracted from a dictionary and three evaluators selected 96 adjectives from those by removing very similar ones in meaning. Two types of 96 7-point scales were conducted to college students for evaluation, whether each adjective describes apartment noise appropriately. From this evaluation, 28 adjectives having above 4.5 points were selected. Again, 8 different types of 7-point scales on 378 adjective pairs(28 x 27/2) were administrated to separate college students to evaluate the degree of similarity between 28 adjectives. Based upon this evaluation, 14 adjectives were finally selected and scores on similarity sere analyzed through two different statistical analyses (Multi-dimensional scale and Cluster analysis). The results showed that three dimensions (displeasure, sensitivity and perceived loudness) exist in peoples' emotional response state to apartment noise. The previous studies have treated annoyance and sensitivity as separate measures to noise. However, this study showed that these two factors were on the same emotional dimension labeled as 'sensitivity' In addition, new dimension, labeled as 'displeasure', was found.

• 한국멀티미디어학회논문지
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• 제17권9호
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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.

• 한국도서관정보학회지
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• 제38권1호
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• pp.89-106
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• 2007

이미 운용되고 있는 우리나라 국립대학 도서관 웹 페이지의 색채이미지를 분석하여, 웹 페이지를 디자인하는데 있어서 배색이미지와 형용사이미지에 관한 정보와 방향을 제시하기 위한 것이다. 분석방법은 색채감성척도를 사용하여 분석대상 사이트에 대한 RGB값을 찾아내어 Color Chip을 추출하였으며, 배색이미지와 형용사이미지로 구분하였다. 연구의 범위는 우리나라 국립대학도서관협의회에 가입되어 있는 41개 국립대학 도서관을 대상으로 하였으며, 그 결과 많은 대학이 흰색이나 회색의 배색 바탕에다, 연한 청색계열의 색조와 녹색계열의 배색이 주를 이루었고, 형용사 이미지는 경쾌한 이미지와 밝은 이미지가 많았으며, 다음으로는 은은한 이미지, 우아한 이미지 순으로 나타났다.

• 한국의류학회지
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• 제27권3_4호
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• pp.418-428
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• 2003

The purpose of this study was to provide the guidance in more objective and proper clothing design reflecting today's consumers' modes in value consumption by identifying the meaning structure and relationship between fashion sensibility and emotion. The stimulus was 54 photos of contemporary costume which represented the Izard' DES. The questionnaire consisted of hi-polar 25 pairs adjective scale of fashion sensibility and the 18 noun scale of emotion was distributed to 970 male and female living in Pusan area. The data were analyzed by Factor analysis, Correlation analysis and Regression analysis using the statistical SPSS package. The major finding of this research were as follows.1. Fashion sensibilities consist of estheticism, maturity, character and feminity to represent 57.17% total varlarlce. 2. Emotions consist of negative emotion, distress afraid, arousal, shame and enjoyment to represent 70.84% total variance. 3. For the relation between fashion sensibility and emotion, they showed significant relationship in most of factors.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.773-777
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• 2009

In recent years, the field of synthesizing voice has been developed rapidly, and the technologies such as reading aloud an email or sound guidance of a car navigation system are used in various scenes of our life. The sound quality is monotonous like reading news. It is preferable for a text such as a novel to be read by the voice that expresses emotions wealthily. Therefore, we have been trying to develop a system reading aloud novels automatically that are expressed clear emotions comparatively such as juvenile literature. At first it is necessary to identify emotions expressed in a sentence in texts in order to make a computer read texts with an emotionally expressive voice. A method on the basis of the meaning interpretation that utilized artificial intelligence technology for a method to specify emotions of texts is thought, but it is very difficult with the current technology. Therefore, we propose a method to determine only emotion every sentence in a novel by a simpler way. This method determines the emotion of a sentence according to an emotion that words such as a verb in a Japanese verb sentence, and an adjective and an adverb in a adjective sentence, have. The emotional characteristics that these words have are prepared beforehand as a emotional words dictionary by us. The emotions used here are seven types: "joy," "sorrow," "anger," "surprise," "terror," "aversion" or "neutral."

• 대한산업공학회지
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• 제31권1호
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• pp.68-78
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• 2005

A new emotion-based image retrieval method is proposed in this paper. The research was motivated by Soen's evaluation of human emotion on color patterns. Thirteen pairs of adjective words expressing emotion pairs such as like-dislike, beautiful-ugly, natural-unnatural, dynamic-static, warm-cold, gay-sober, cheerful-dismal, unstablestable, light-dark, strong-weak, gaudy-plain, hard-soft, heavy-light are modeled by 19-dimensional color array and $4{\times}3$ gray matrix in off-line. Once the query is presented in text format, emotion model-based query formulation produces the associated color array and gray matrix. Then, images related to the query are retrieved from the database based on the multiplication of color array and gray matrix, each of which is extracted from query and database image. Experiments over 450 images showed an average retrieval rate of 0.61 for the use of color array alone and an average retrieval rate of 0.47 for the use of gray matrix alone.