• Journal of the Korean Society of Costume
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• v.61 no.2
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• pp.47-59
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• 2011

This study provides a systematic investigation about objective personal image consulting, tool development and image-making research by analyzing the status of the Korean image-consulting industry and education. For the research, we carried out literature surveys of books on image consulting and previous research reports. In particular, we surveyed image consulting businesses that have internet web sites, and educational institutes. The results of the survey are as follows: First, domestic image consulting businesses in Korea are investigated about 93 private companies and 4 associations. They do the image making, color consulting, and education for individuals and business. Second, professional image consulting education is carried out not only in the 93 private companies, but also in the continuing and professional studies for adults of 10 universities. Furthermore, more then 90 universities have specific academic programs related to the image consulting such as facial management, beauty coordination, cosmetology, stylists, fashion events, broadcasting stylists, and so on. Third, a typical image consulting job is the personal shoppers who assists VIP customers in department stores. Professionals and politicians have personal fashion stylists for their image making. Today, the job has expanded to public fashion therapist. Fourth, the contents of an image consulting education have appeared in similar industries and educations. These contents include fashion styles, personal color analysis, make-up, facial expressions, gestures, perfumes, accessories, etc. This study is based on research on the current Korean image-consulting industry, and will enable follow-up details to be implemented. using the basis of this study for a strategic self-image formation system.

• Journal of Internet Computing and Services
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• v.8 no.6
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• pp.155-167
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• 2007

There are four types of human beings according to the Sasang Typology, Oriental medical doctors frequently prescribe healthcare information and treatment depending on one's type, The feature ratios (Table 1) on the human face are the most important criterions to decide which type a patient is. In this paper, we proposed a system to extract these feature ratios from the people's side face, There are two challenges in acquiring the feature ratio: one that selecting representative features; the other, that detecting region of interest from human profile facial image effectively and calculating the feature ratio accurately. In our system, an adaptive color model is used to separate human side face from background, and the method based on geometrical model is designed for region of interest detection. Then we present the error analysis caused by image variation in terms of image size and head pose, To verify the efficiency of the system proposed in this paper, several experiments are conducted using about 173 korean's left side facial photographs. Experiment results shows that the accuracy of our system is increased 17,99% after we combine the front face features with the side face features, instead of using the front face features only.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.361-368
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• 2017

This study analyzes into the characteristic appearance in distintion with emotional changes toward visual forms of psychology along with character development in the 3D animation industry. In this regard, the study seeks to propose essential targets of the five emotional characters from the Pixar's animation Inside-Out to prove psychological effects to the character's visual appearance. As a previous research, the study analysis the visual representations oriented toward both emotional facial expression and emotional color expression using both Paul Ekman and Robert Plutchik's human basic emotion research. The purpose of this study is to present the visual guideline of emotional character's appearance through the various human expression for differentiated character development in animation production.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.46-51
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• 2002

In this paper, I proposed a eyebrow detection algorithm in human face, that is important element in facial recognition. The proposed algorithm consists of four processes: face region detection using color region segmentation. eye detection by template matching, eyebrow candidate region detection in detected eye region, and eyebrow detection by thresholding using the modified histogram that gets luminance value in the candidate region. The test results show that the proposed algorithm can detect eyebrow region very effectively in facial image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10C
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• pp.983-991
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• 2005

Human faces are commonly found in a video such as a drama and provide useful information for video content analysis. Therefore, face detection plays an important role in applications such as face recognition, and face image database management. In this paper, we propose a face detection algorithm based on pre-processing of scene change detection for indexing and cast searching in video. The proposed algorithm consists of three stages: scene change detection stage, face region detection stage, and eyes and mouth detection stage. Experimental results show that the proposed algorithm can detect faces successfully over a wide range of facial variations in scale, rotation, pose, and position, and the performance is improved by $24\%$with profile images comparing with conventional methods using color components.

• Journal of Fashion Business
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• v.24 no.6
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• pp.120-134
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• 2020

Recently, the beauty industry has implemented personalized services based on skin big data. To increase competitiveness in the beauty industry, systematic data measurement and evaluation indicators are necessary to select data and obtain necessary knowledge. In response, this study sought to stably enhance the accuracy of skin diagnosis based on satisfaction and reliability. To this end, the research was conducted through focus group interviews (FGI), a case study of brands, and analysis of prior research results. In particular, as a result of analyzing keywords that classify skin types by brand, common survey items for skin types were oiliness and using moisturizer, cosmetic use and vascular of skin, external stimulus and blemish & freckles, facial wrinkle, outside activities, self-consciousness, and smoke. In additioin to the common questions of the preceding study and the brand survey items, the questions concerning complex skin types, seasonal change, facial color, wrinkles and elasticity were added, and the questions were presented in a total of 40 items. In particular, it suggested that skin measurement could be conducted by focusing on elasticity and pigmentation items by reflecting the results of prior research and the opinions of FGI, and based on this, a customized service with high satisfaction and high accuracy of beauty care based on this could be proposed. We hope that this study will facilitate active self-care by providing more satisfying skin stones and personalized cosmetics proposals, thus laying the foundation for the further development of the cosmetics industry.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.75-83
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• 2008

We propose a welfare interface using multiple fecial features tracking, which can efficiently implement various mouse operations. The proposed system consist of five modules: face detection, eye detection, mouth detection, facial feature tracking, and mouse control. The facial region is first obtained using skin-color model and connected-component analysis(CCs). Thereafter the eye regions are localized using neutral network(NN)-based texture classifier that discriminates the facial region into eye class and non-eye class, and then mouth region is localized using edge detector. Once eye and mouth regions are localized they are continuously and correctly tracking by mean-shift algorithm and template matching, respectively. Based on the tracking results, mouse operations such as movement or click are implemented. To assess the validity of the proposed system, it was applied to the interface system for web browser and was tested on a group of 25 users. The results show that our system have the accuracy of 99% and process more than 21 frame/sec on PC for the $320{\times}240$ size input image, as such it can supply a user-friendly and convenient access to a computer in real-time operation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7C
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• pp.565-575
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• 2012

In the modern everyday life, cars the largest proportion of smart features that require mounting in a variety of smart devices and smart methods on have been developed. In this paper, the smart car among the main core of the safety management system optional for the control of drinking and drowsiness, as part of system development, will be drinking if you start your car automatically is to develop a system to avoid driving. For this, through image processing to analyze the driver's seat of the driver's facial color how to determine whether or not drinking alcohol is proposed. In particular, the system developed in this paper determines whether or not drinking alcohol before the face images without the need for alcohol after only a unique color change of the face appears to target only way to determine whether drinking and actual alcohol control center of a smart car safety control management system can be applied effectively. The experiment was done in 30 patients after drinking appears face color changes of them. We also perform an analysis on the statistical significance of the experimental results to verify the effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.133-138
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• 2008

In this paper, we propose a novel anchor shot detection system, named to MASD (Multi-phase Anchor Shot Detection), which is a core step of the preprocessing process for the news video analysis. The proposed system is composed of four modules and operates sequentially: 1) skin color detection module for reducing the candidate face regions; 2) face detection module for finding the key-frames with a facial data; 3) vector representation module for the key-frame images using a non-negative matrix factorization; 4) one class SVM module for determining the anchor shots using a support vector data description. Besides the qualitative analysis, our experiments validate that the proposed system shows not only the comparable accuracy to the recently developed methods, but also more faster detection rate than those of others.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.206-211
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• 2020

It is Face recognition is a very important process in image monitoring and it is a form of biometric technology. The recognition process involves many variables and is highly complex, so the software development has only begun recently with the development of hardware. Face detection technology using the CCTV is a process that precedes face analysis, and it is a technique that detects where the face is in the image. Research in face detection and recognition has been difficult because the human face reacts sensitively to different environmental conditions, such as lighting, color of skin, direction, angle and facial expression. The utility and importance of face recognition technology is coming into the limelight over time, but many aspects are being overlooked in the facial area detection technology that must precede face recognition. The system in this paper can detect tilted faces that cannot be detected by the AdaBoost detector and It could also be used to detect other objects.