• Science of Emotion and Sensibility
• /
• v.13 no.3
• /
• pp.493-500
• /
• 2010

The development of new technology and diversity in user needs lead mobile phone manufacturers to establish new strategies different from the existing for user attraction. Product identity, and brand image are major strategies for differentiation and adding new values to a product. This research starts with stating emotional brand image as the brand image made by the actual usage and the emotion built from the experience while using the product. This research will compare emotional brand image of the three major mobile phone manufactures in Korea (Brand A, C, and S) using evaluation of six representative emotions from users while using the product. The result of evaluating actual mobile phone users and the emotion built while actually using the product showed the brand image, and especially the emotional side of Korean mobile phone manufacturers. The result of this research itself would not be sufficient to simply state the emotional brand image of Korean mobile phone manufactures, but with further research including age, profession, gender and other demographic factors the result of this research would surely be able to abstract a clearer view of emotional brand image of Korean mobile phone manufactures.

• Science of Emotion and Sensibility
• /
• v.20 no.1
• /
• pp.57-66
• /
• 2017

Emotional image quality optimization methodologies are investigated using technological image quality controls based on the eye tests of various image samples. The images are evaluated based on various contrast, lightness and saturation image quality metric tone curves. The order of importance to image quality enhancements is contrast, saturation and brightness. The slopes of emotional image qualities with respect to technical image quality metric changes are found to be composed of mathematical function modelling with nearly zero, intermediate and maximum slope regions in general, which can reflect well known log and saturated as well as conventional reverse U shape natures. Image quality improvements are analyzed not only with just single but also with multiple image quality metrics. To ease the unified image quality metric analysis and control, a new function is presented to utilize both the newly found and conventional emotional image quality behaviors. It is found that the overall image quality enhancement can be realized only in a few limited cases of multiple image quality metric controls. It is also found that the kinds of image quality enhancement methodologies are not strongly dependent on image contents (genre).

• Journal of Digital Convergence
• /
• v.16 no.4
• /
• pp.313-319
• /
• 2018

This experimental research explores the effect of drone's moving image on media audience's flow, arousal of interest and emotional state. Most previous researchers of media image effect insisted that camera movement should be abstained in order to give audience the feeling that movement of figures is in the contents story itself. and camera movement also can disturb natural viewing of audience. For the purpose of finding the effect of drone's moving image on media audience's flow, arousal of interest and emotional state, 2 groups of subjects composed of 56 university students were exposed to 2 different video clips, one with moving drone's image, the other with hovering drone's image. After this experiment, Questions which were designed to measure audience's flow, arousal of interest and emotional state were asked and analysed. This research found that subjects exposed to moving drone's image felt more interested and more positive emotional state than subjects exposed to hovering drone's image. However meaningful effect of drone's moving image on audience's flow was not found.

• Fashion & Textile Research Journal
• /
• v.21 no.1
• /
• pp.104-111
• /
• 2019

This study was developed using the DTP (digital textile printing) jacquard fabrics with a three-dimensional pattern for bag and evaluated the preference and emotional structure. The following conclusions were obtained. Three-dimensional patterns of 12 species using the illustrator program, including six kinds of designs based on the text and six kinds of character types based on the geometry of the basic design was developed. As a result of evaluating the preference of the three-dimensional pattern jacquard fabric, the most preferred fabric was a three-dimensional patterned jacquard fabric with a motif of the Korean consonant "ㅅ". The results of analyzing the emotional dimension of the three-dimensional pattern jacquard fabric, eight factors including simple image, feminine image, exotic image, graphic image, sporty image, masculine image, dynamic image and stereoscopic image were derived. Between emotional factors and preferences correlation analysis showed the stronger the simple image, the feminine image, and the sporty image, the more preferable. It suggested the possibility of a morphological and new fabric for bag, textile design motifs by using Hangul consonants attempt to limit the flatness of the existing geometric form patterns that can be applied to three-dimensional bag whether swirly patterns overcome.

• Fashion & Textile Research Journal
• /
• v.17 no.4
• /
• pp.524-540
• /
• 2015

This study develops textile pattern design ideas created through the visualization of music. Methods of auditory and synesthesia were employed to analyze various attributes of popular music genres and appoint language image, shape image, and color image to obtain their interrelationships. This study provides data that can be used to express emotional images on textile print pattern designs. This research used different genres of popular music as stimuli. The language image was extracted and introduced to the overall color scheme; in addition, the color image was verified. The analysis of the color image was executed by applying it with the color set image scale of I.R.I colors. Then, the color image of the target genre of popular music was examined and analyzed through a color tone system. The preference in shape image was realized through visual images based on basic principles of points, lines, and sides composition; subsequently, an analysis of the emotional image of popular music followed. An examination of the emotional images of different popular music genres have led to the discovery that language image, color image, and shape image all share a common emotional image. There was also a realization that similarity and interrelationship exists in language, color, and shape images experienced by listening to popular music.

• The Journal of the Korea Contents Association
• /
• v.13 no.11
• /
• pp.562-570
• /
• 2013

Image of emotional pleasure or displeasure, tension or emotional division of tranquility in the form of a tree is evaluated by weighting. Image representative evaluation of the sensitivity of the brightness contrast ratings 1 car pleasure, displeasure or stress or emotional tranquility and two cars are separated by image segmentation. Emotion Recognition of four compared to the numerical data is measured by brightness. OpenCV implementation through evaluation graph the stress intensity contrast, tranquility, pleasure, displeasure, depending on changes in the value of the computing is divided into four emotional. Contrast sensitivity of computing the brightness depending on the value entered 'nuisance' to 'excellent' or 'stress' to 'calm' the emotional changes can give. Calculate the sensitivity of the image regularity of localized computing system can control the future direction of industry on the application of emotion recognition will play a positive role.

• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.562-566
• /
• 2009

In this paper, we present a novel system to categorize web image search results using emotional concepts and to browse the results more conveniently and easily. The proposed system can categorize search results into 8 emotional categories based on emotion vector, which obtained by color and pattern features. Here, we use Kobayashi’s emotional categories: {romantic, natural, casual, elegant, chic, classic, dandy and modern}. With search results for a given query, the proposed system can provide categorized images for each emotional category. With 1,000 Yahoo! search images, we compared the proposed method with Yahoo! image search engine in respect of satisfaction, efficiency, convenience and relevance with a user study. Our experimental results show the effectiveness of the proposed method.

• Journal of Korean Society for Quality Management
• /
• v.41 no.2
• /
• pp.261-276
• /
• 2013

Purpose: This study intends to offer strategic implications that can be used in Korean medicine hospitals through analysis of causal relationship among factors focusing on image improvement and trust building. Methods: Differential model was introduced to test causal relationship. Questionnaire was developed, and data was collected and analyzed with Structural Equation Modeling. Results: Medical service has effects on image, trust, and CS. CS has an effect on trustworthiness, and trustworthiness has positive effect on loyalty intention and has negative effect on switching intention. Emotional attachment has moderating functions between trust and loyalty intention and between trust and switching intention. Conclusion: This study offers practical implications to relevant managers, at the same time it has limitations that omits relevant study of inducing factor for emotional attachment.

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2004.05a
• /
• pp.178-179
• /
• 2004

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.10
• /
• pp.957-962
• /
• 2010

If we want to recognize the human's emotion via the facial image, first of all, we need to extract the emotional features from the facial image by using a feature extraction algorithm. And we need to classify the emotional status by using pattern classification method. The AAM (Active Appearance Model) is a well-known method that can represent a non-rigid object, such as face, facial expression. The Bayesian Network is a probability based classifier that can represent the probabilistic relationships between a set of facial features. In this paper, our approach to facial feature extraction lies in the proposed feature extraction method based on combining AAM with FACS (Facial Action Coding System) for automatically modeling and extracting the facial emotional features. To recognize the facial emotion, we use the DBNs (Dynamic Bayesian Networks) for modeling and understanding the temporal phases of facial expressions in image sequences. The result of emotion recognition can be used to rehabilitate based on biofeedback for emotional disabled.