• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.608-612
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• 2002

An automatic face and facial feature points(FFPs) detection system is proposed. A face is represented as a graph where the nodes are placed at facial feature points(FFPs) labeled by their Gabor features md the edges are describes their spatial relations. An innovative flexible feature matching is proposed to perform features correspondence between models and the input image. This matching model works likes random diffusion process in the image spare by employing the locally competitive and globally corporative mechanism. The system works nicely on the face images under complicated background, pose variations and distorted by facial accessories. We demonstrate the benefits of our approach by its implementation on the fare identification system.

• Journal of Sasang Constitutional Medicine
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• v.34 no.4
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• pp.68-80
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• 2022

Objectives This study is to report a significant improvement in a Taeeumin patient with systemic contact dermatitis after eating urushiol chicken by herbal medicine treatment. Methods The patient had complaints of erythema, swelling, pruritus, scaly skin, and facial flushing. We treated the patient with an herbal medicine 'Galgeunhaegi-tang' for three months. We evaluated the treatment outcome of systemic contact dermatitis using the Three Item Severity(TIS) score every visit and facial flushing by Image color summarizer at the first and last visit. Results After the treatment, the severity of the patient's skin complaints lessened from moderate to mild. The Image color summarizer showed a minor decrease in the normalized red color level and a significant increase in the brightness level and facial color percentage. Conclusions The patient diagnosed with systemic contact dermatitis, treated with Galgeunhaegi-tang for three months, showed a significant improvement in skin complaints with brighter and even facial color.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.200-203
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• 2021

This paper introduces a smart mirror technology that recognizes a person's facial expressions through image classification among several artificial intelligence technologies and presents them in a mirror. 5 types of facial expression images are trained through artificial intelligence. When someone looks at the smart mirror, the mirror recognizes my expression and shows the recognized result in the mirror. The dataset fer2013 provided by kaggle used the faces of several people to be separated by facial expressions. For image classification, the network structure is trained using convolution neural network (CNN). The face is recognized and presented on the screen in the smart mirror with the embedded board such as Raspberry Pi4.

• Journal of the Korean Society of Costume
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• v.65 no.3
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• pp.1-14
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• 2015

The purpose of this study is to identify cross-cultural features among Korea, China, and Japan by comparing differences in facial awareness, attractiveness preferences, and consideration of facial parts in a group of Korean, Chinese, and Japanese men and women as they evaluated the faces of Korean women in their 20s. A survey was conducted targeting male and female Korean, Chinese, and Japanese college students in their 20s. Frequency analysis, ANOVA, Duncan test, factorial analysis, and reliability analysis, MANOVA were carried out using SPSS 18.0. The results of this study are as follows: Faces of Korean women in their 20s were evaluated by Korean, Chinese, and Japanese men and women in their 20s and were classified into four categories as 'Youthfulness', 'Classiness', 'Friendliness' and 'Activeness'. Differences in facial image awareness were observed depending on nationality and gender. Korean participants were found to place importance on overall morphological factors; The Japanese focused on the eyes; and the Chinese on the skin color. Women of all nationalities showed, on average, a higher awareness of facial parts than men. No significant differences in facial attractiveness preferences were found based on nationality or gender, but there were differences in how the participants evaluated faces for attractiveness, showing that reasons for preferences may vary even if the preferences are the same.

• Journal of KIISE
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• v.44 no.7
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• pp.692-702
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• 2017

Face detection using the LBP based feature descriptor has issues in that it can not represent spatial information between facial shape and facial components such as eyes, nose and mouth. To address these issues, in previous research, a facial image was divided into a number of square sub-regions. However, since the sub-regions are divided into different numbers and sizes, the division criteria of the sub-region suitable for the database used in the experiment is ambiguous, the dimension of the LBP histogram increases in proportion to the number of sub-regions and as the number of sub-regions increases, the sensitivity to facial orientation rotation increases significantly. In this paper, we present a novel facial region segmentation method that can solve in-plane rotation issues associated with LBP based feature descriptors and the number of dimensions of feature descriptors. As a result, the proposed method showed detection accuracy of 99.0278% from a single facial image rotated in orientation.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.1-5
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• 2009

This paper suggests to apply mirror-reflected method based 2D emotion recognition database to 3D application. Also, it makes facial expression of fuzzy modeling using probability of emotion. Suggested facial expression function applies fuzzy theory to 3 basic movement for facial expressions. This method applies 3D application to feature vector for emotion recognition from 2D application using mirror-reflected multi-image. Thus, we can have model based on fuzzy nonlinear facial expression of a 2D model for a real model. We use average values about probability of 6 basic expressions such as happy, sad, disgust, angry, surprise and fear. Furthermore, dynimic facial expressions are made via fuzzy modelling. This paper compares and analyzes feature vectors of real model with 3D human-like avatar.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.1-9
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• 2015

In this paper, a study on facial movements are analyzed in terms of opposite emotion stimuli by image processing of Kinect facial image. To induce two opposite emotion pairs such as "Sad - Excitement"and "Contentment - Angry" which are oppositely positioned onto Russell's 2D emotion model, both visual and auditory stimuli are given to subjects. Firstly, 31 main points are chosen among 121 facial feature points of active appearance model obtained from Kinect Face Tracking SDK. Then, pixel changes around 31 main points are analyzed. In here, local minimum shift matching method is used in order to solve a problem of non-linear facial movement. At results, right and left side facial movements were occurred in cases of "Sad" and "Excitement" emotions, respectively. Left side facial movement was comparatively more occurred in case of "Contentment" emotion. In contrast, both left and right side movements were occurred in case of "Angry" emotion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1310-1318
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• 2002

In this study, we developed a 3D facial modeler and animator that will not use the existing method by 3D scanner or camera. Without expensive image-input equipments, we can easily create 3D models only using front and side images. The system is available to animate 3D facial models as we connect to animation server on the WWW which is independent from specific platforms and softwares. It was implemented using Java 3D API. The facial modeler detects MPEG-4 FDP(Facial Definition Parameter) feature points from 2D input images, creates 3D facial model modifying generic facial model with the points. The animator animates and renders the 3D facial model according to MPEG-4 FAP(Facial Animation Parameter). This system can be used for generating an avatar on WWW.

• Journal of Korean Dental Science
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• v.17 no.1
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• pp.1-13
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• 2024

With the advances of digital scanning technology in dentistry, the interests in facial scanning in orthodontics have increased. There are many different manufacturers of facial scanners marketing to the dental practice. How do you know which one will work best for you? What questions should you be asking? We suggest a clinical guideline which may help you make an informed decision when choosing facial scanners. The characteristics of 7 facial scanners were discussed in this article. Here are some considerations for choosing a facial scanner. *Accuracy: For facial scanners to be of real value, having an appropriate camera resolution is necessary to achieve more accurate facial image representation. For orthodontic application, the scanner must create an accurate representation of an entire face. *Ease of Use: Scanner-related issues that impact their ease of use include type of light; scan type; scan time; file type generated by the scanner; unit size and foot print; and acceptance of scans by third-party providers. *Cost: Most of the expenses associated with facial scanning involve the fixed cost of purchase and maintenance. Other expenses include technical support, warranty costs, transmission fees, and supply costs. This article suggests a clinical guideline to make the right choice for facial scanner in orthodontics.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.107-114
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• 2016

Recently, 3D related technology has become a hot topic for IT. 3D technologies such as 3DTV, Kinect and 3D printers are becoming more and more popular. According to the flow of the times, the goal of this study is that the general public is exposed to 3D technology easily. we have developed a web-based application program that enables 3D modeling of facial front and side photographs using a mobile phone. In order to realize 3D modeling, two photographs (front and side) are photographed with a mobile camera, and ASM (Active Shape Model) and skin binarization technique are used to extract facial height such as nose from facial and side photographs. Three-dimensional coordinates are generated using the face extracted from the front photograph and the face height obtained from the side photograph. Using the 3-D coordinates generated for the standard face model modeled with the standard face as a control point, the face becomes the face of the subject when the RBF (Radial Basis Function) interpolation method is used. Also, in order to cover the face with the modified face model, the control point found in the front photograph is mapped to the texture map coordinate to generate the texture image. Finally, the deformed face model is covered with a texture image, and the 3D modeled image is displayed to the user.