• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.187-194
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• 2013

The final aim of the present study is to build a system of converting a color image into musical elements based on a synesthetic perception, emulating human synesthetic skills, which make it possible to associate a color image with a specific sound. This can be done on the basis of the similarities between physical frequency information of both light and sound. As a first step, an input true color image is converted into hue, saturation, and intensity domains based on a color model conversion theory. In the next step, musical elements including note, octave, loudness, and duration are extracted from each domain of the HSI color model. A fundamental frequency (F0) is then extracted from both hue and intensity histograms. The loudness and duration are extracted from both intensity and saturation histograms, respectively. In experiments, the proposed system on the conversion of a color image into musical elements was implemented using standard C and Microsoft Visual C++(ver. 6.0). Through the proposed system, the extracted musical elements were synthesized to finally generate a sound source in a WAV file format. The simulation results revealed that the musical elements, which were extracted from an input RGB color image, reflected in its output sound signals.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.154-161
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• 2008

In this paper, a novel method is proposed using color and pattern information for recognizing some emotions included in a fertile. Here we use 10 Kobayashi emotion to represent emotions. - { romantic, clear, natural, casual, elegant chic, dynamic, classic, dandy, modem } The proposed system is composed of feature extraction and classification. To transform the subjective emotions as physical visual features, we extract representative colors and Patterns from textile. Here, the representative color prototypes are extracted by color quantization method, and patterns exacted by wavelet transform followed by statistical analysis. These exacted features are given as input to the neural network (NN)-based classifiers, which decides whether or not a textile had the corresponding emotion. When assessing the effectiveness of the proposed system with 389 textiles collected from various application domains such as interior, fashion, and artificial ones. The results showed that the proposed method has the precision of 100% and the recall of 99%, thereby it can be used in various textile industries.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.584-591
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• 2014

This article discussed emotion and communication at the film editing theory. By editing as a form of communication, audiences response to the new facts of the story or the new shot as its details and then it uses their ability to induce. Lev Kuleshov, by the famous Mozhukin experiment, intended to show that montage draw spectator's inferences on emotion and association beyond content of the individual shots. The continuous editing technologies such as 180-degree rule, matching eye-view and behavior, 30-degree rule, and continuity of sound, light and color, enhance emotion. Point-of-view editing is the main device to maximize the film's emotion. Point-of-view editing serving the purpose of the film narration is a powerful means to practice and to persuade emotion communication.

• Korean Institute of Interior Design Journal
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• no.31
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• pp.64-70
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• 2002

One of the main motivations of this research process is to develop an adaptable VR model whose color can be changed according to the emotional information of user. This paper addresses how to define color scheme and combine colors with harmony. The adaptable color of the VR model consists of three processes: emotional keyword identification, the color combination and the VR model adaptation processes. We have used the biorhythm to derive the emotional keyword which is used to find the color harmony scheme. The color harmony scheme provides information for the color combination of the VR model. Finally, we have obtained the VR model which color has been changed using the identified color schema.

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

• 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.

• Science of Emotion and Sensibility
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• v.7 no.4
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• pp.57-65
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• 2004

In this paper, we present a hybrid approach which incorporates color, texture and shape in content-based image retrieval. Colors in each image are clustered into a small number of representative colors. The feature descriptor consists of the representative colors and their percentages in the image. A similarity measure similar to the cumulative color histogram distance measure is defined for this descriptor. The co-occurrence matrix as a statistical method is used for texture analysis. An optimal set of five statistical functions are extracted from the co-occurrence matrix of each image, in order to render the feature vector for eachimage maximally informative. The edge information captured within edge histograms is extracted after a pre-processing phase that performs color transformation, quantization, and filtering. The features where thus extracted and stored within feature vectors and were later compared with an intersection-based method. The content-based retrieval system is tested to be effective in terms of retrieval and scalability through experimental results and precision-recall analysis.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.559-572
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• 2010

Color, an important visual cue, can cross-modally affect odor association and odor quality identification Here, this research investigates aspects of the cross-modal associations between color and fragrance in greater depth, delving into the topic of whether the degree-of-association of fragrances with hue and tone of colors varies systematically. For 33 color stimuli (10 hues, 3 tones, and 3 achromatic colors), 67 subjects judged the degree-of-association of four typical fragrance families (fresh, floral, oriental, and woody) on a 7-point scale. The statistical analysis showed that fragrance associations of the all families had characteristic distributions across ten hues of the color stimuli. The cross-modal relationship between color tone (especially, lightness attribute) and fragrance association appeared to be dimensional (e.g. a positive linear relationship between the floral family and the lightness). More specifically, as colors became warmer and brighter, the associated floral scents were stronger, while the woody scents was less associated. Brighter or more vivid cool colors were associated with stronger fresh scents. These findings confirm the systematic existence of synthetic interactions between vision and olfaction in perfumery.

• Science of Emotion and Sensibility
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• v.14 no.1
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• pp.127-136
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• 2011

The objectives of this study were to investigate the effects of color characteristics on tactile sensation / sensibility image of silk fabrics and to provide prediction models for their tactile sensation/sensibility image by both mechanical properties and color characteristics. As results, some of tactile sensation/sensibility terms including 'smooth', 'buoyant', 'thick', 'stiff', 'unique', 'casual', 'rural', and 'modern' seemed to be influenced by color characteristics such as achromatic/chromatic and hue / tone as well as by mechanical properties of silk. Moreover, red or green silk was more strongly felt than gray ones for 'thick' and 'stiff' as well as pale or vivid was. On the other hands, 'Rural' and 'casual' were respectively evaluated more highly for green, pale, or vivid silk. These results imply that color could give an effect on subjective tactile sensation / sensibility. Finally, prediction models for some of tactile sensation / sensibility of silk fabrics by both mechanical properties and color characteristics were established.

• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.73-92
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• 2020

This article addresses the possibility of developing a new art appreciation method using olfaction, which was not previously considered an important sense in expanding the cultural enjoyment of visually impaired people. The human olfactory system is a faculty that is not considered very important in modern society; however, this is due to cultural factors, and from a biological point of view, the human sense of smell has sufficient potential for practical application. In this study, it is assumed that when various types of scent are perceived through this sense of smell, each has its own unconscious relation to color and concept, which researchers have termed "color directivity" and "concept directivity." Through experiments, the researchers found that some specific scents have color directivity and concept directivity, and in using these scents, they succeeded in delivering information about colors used in artworks to the visually impaired. Based on this study, we hope to continue our research on the use of color-concept directional scents that can convey the brightness and saturation of colors and more diverse hues.