• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.412-414
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• 2001

In this paper, we describe an real-time facial feature tracker. We only used a general USB PC Camera without a frame grabber. The system has achieved a rate of 8+ frames/second without any low-level library support. It tracks pupils, nostrils and corners of the lip. The signal from USB Camera is YUV 4:2:0 vertical Format. we converted the signal into RGB color model to display the image and We interpolated V channel of the signal to be used for extracting a facial region. and we analysis 2D blob features in the Y channel, the luminance of the image with geometric restriction to locate each facial feature within the detected facial region. Our method is so simple and intuitive that we can make the system work in real-time.

• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.37-43
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• 2014

In this paper, we propose a robust lip detection algorithm using color clustering. At first, we adopt AdaBoost algorithm to extract facial region and convert facial region into Lab color space. Because a and b components in Lab color space are known as that they could well express lip color and its complementary color, we use a and b component as the features for color clustering. The nearest neighbour clustering algorithm is applied to separate the skin region from the facial region and K-Means color clustering is applied to extract lip-candidate region. Then geometric characteristics are used to extract final lip region. The proposed algorithm can detect lip region robustly which has been shown by experimental results.

• Journal of the Korea Computer Industry Society
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• v.2 no.3
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• pp.265-274
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• 2001

In this paper, we propose a content-based face retrieval system which can retrieve a face based on a facial feature region. Instead of using keyword such as a resident registration number or name for a query, the our system uses a facial image as a visual query. That is, we recognize a face based on a specific feature region including eyes, nose, and mouth. For this, we extract the feature region using the color information based on HSI color model and the edge information from wavelet transformed image, and then recognize the feature region using neural network. The proposed system is implemented on client/server environment based on Oracle DBMS for a large facial image database. In the experiment with 150 various facial images, the proposed method showed about 88.3% recognition rate.

• Journal of Acupuncture Research
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• v.40 no.4
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• pp.319-328
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• 2023

Facial nerve palsy refers to sudden, unilateral lower motor neuron facial paralysis. This study aimed to determine the importance of neck treatment in the treatment of facial paralysis. A literature search was performed on six online databases and other sources until January 15, 2023. A total of 426 papers were retrieved. After excluding duplicated and inconsistent papers, papers not including cervical treatment, and experimental papers on animals, two papers were finally selected. The type of treatment method, therapeutic effects, assessment of the risk of bias in randomized controlled trials, and non-randomized controlled trials and side effects were evaluated. Chiropractic, manual therapy, facial meridian massage, and acupotomy were applied to the face and cervical spine region. The results showed that each treatment had a significant therapeutic effect through evaluation index measurement methods, such as the visual analog scale and Yanagihara's unweighted regional grading system. This study demonstrated the importance of the cervical spine area in the treatment of facial paralysis. However, this study has many limitations. Thus, high-quality randomized controlled comparative studies on the treatment of the cervical spine area only or studies that include cervical spine area treatment as an interventional treatment while performing oriental or comprehensive treatment are needed.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.192-200
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• 2009

In this paper, we report the progress in the development of performance evaluation method for detection algorithms of face region and facial components. This paper aims to provide a standardized evaluation method for general approach in face recognition application as a potential component in futuristic intelligent robot systems. From an image capture process to the retrieval of face-related information, all the necessary steps are shown with examples.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.45-52
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• 2000

In this study, we propose the image segmentation algorithm for facial region segmentation. The proposed algorithm separates the mean image of low frequency band from the differential image of high frequency band in order to make a boundary using HWT, and then we reduce the isolation pixels, projection pixels, and overlapped boundary pixels from the low frequency band. Also the boundaries are detected and simplified by the proposed boundary detection algorithm, which are cleared on the thinning process of 1 pixel unit. After extracting facial image boundary by using the proposed algorithm, we make the mask and segment facial image through matching original image. In the result of facial region segmentation experiment by using the proposed algorithm, the successive facial segmentation have 95.88% segmentation value.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1257-1263
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• 2006

Many automatic medical devices have been invented and developed mostly for the western medicine, not for the oriental medicine. Facial ocular inspection is one of the four diagnosis methods of oriental medicine, which makes a diagnosis of disease by observing the shape and color of patient's vital organs. In facial ocular inspection, the regions of five sensory organs and Myungdang are specially important. In this paper, we propose a novel method to extract the five sensory organ and Myungdang from a facial image for facial ocular inspection. Finally, we show the usefulness of the proposed method by experiments.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.594-600
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• 2003

In this paper, we propose a detection method for facial features in color images with various backgrounds and face poses. To begin with, the proposed method extracts face candidacy region from images with various backgrounds, which have skin-tone color and complex objects, via the color and edge information of face. And then, by using the elliptical shape property of face, we correct a rotation, scale, and tilt of face region caused by various poses of head. Finally, we verify the face using features of face and detect facial features. In our experimental results, it is shown that accuracy of detection is high and the proposed method can be used in pose-invariant face recognition system effectively

• Genomics & Informatics
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• v.11 no.2
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• pp.83-92
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• 2013

Genetic studies on facial morphology targeting healthy populations are fundamental in understanding the specific genetic influences involved; yet, most studies to date, if not all, have been focused on congenital diseases accompanied by facial anomalies. To study the specific genetic cues determining facial morphology, we estimated familial correlations and heritabilities of 14 facial measurements and 3 latent factors inferred from a factor analysis in a subset of the Korean population. The study included a total of 229 individuals from 38 families. We evaluated a total of 14 facial measurements using 2D digital photographs. We performed factor analysis to infer common latent variables. The heritabilities of 13 facial measurements were statistically significant (p < 0.05) and ranged from 0.25 to 0.61. Of these, the heritability of intercanthal width in the orbital region was found to be the highest ($h^2$ = 0.61, SE = 0.14). Three factors (lower face portion, orbital region, and vertical length) were obtained through factor analysis, where the heritability values ranged from 0.45 to 0.55. The heritability values for each factor were higher than the mean heritability value of individual original measurements. We have confirmed the genetic influence on facial anthropometric traits and suggest a potential way to categorize and analyze the facial portions into different groups.

• Journal of IKEEE
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• v.26 no.3
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• pp.430-436
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• 2022

In this paper, we propose an intelligent camera for multiple body temperature detection. The proposed camera is composed of optical(4056*3040) and thermal(640*480), which detects abnormal symptoms by analyzing a person's facial expression and body temperature from the acquired image. The optical and thermal imaging cameras are operated simultaneously and detect an object in the optical image, in which the facial region and expression analysis are calculated from the object. Additionally, the calculated coordinate values from the optical image facial region are applied to the thermal image, also the maximum temperature is measured from the region and displayed on the screen. Abnormal symptom detection is determined by using the analyzed three facial expressions(neutral, happy, sadness) and body temperature values. In order to evaluate the performance of the proposed camera, the optical image processing part is tested on Caltech, WIDER FACE, and CK+ datasets for three algorithms(object detection, facial region detection, and expression analysis). Experimental results have shown 91%, 91%, and 84% accuracy scores each.