• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.436-438
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• 2001

본 논문에서는 기울어진 얼굴 영상에서 얼굴 구성 요소를 추출하는 방법을 제안한다. 제안하는 방법은 먼저 피부 색상 정보를 이용하여 얼굴 후보 영역을 추출한다. 이때 YIQ 색상 좌표계를 이용하고 조명의 영향을 반영하기 위하여 피부색상 영역을 다단계로 분할하여 색상 영역을 각각 결정한 뒤 적중률을 계산하여 얼굴 후보 영역을 결정하는 방법을 제안하였다. 2단계에서는 얼굴의 구성 요소중 가장 두드러진 특징인 눈동자 영역을 기준으로 한국인의 표준 얼굴 통계치를 적응하여 탐색하는 방법을 사용하였다. 이때 탐색된 눈동자 좌표로부터 얼굴의 기울기를 추정한다. 다음 단계에서는 얼굴 후보 영역에 대하여 기울어짐 보정을 수행한 뒤, 수평 수직 투영값을 이용하여 얼굴의 구성요소를 탐색한 뒤 얼굴 포함 최소 사각형을 정의하였다. 마지막으로 얼굴 영상 데이터 베이스로부터 얼굴 포함 최소 사각형에 대한 명암값 표준템플릿을 정의하고, 입력 영상에서 탐색된 최소 포함 사각형에 대하여 얼굴 영역 검증하는 방법을 제안하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1329-1332
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• 2000

캐리커처 생성 시스템은 입력된 인물 사진을 세그먼테이션을 통하여 특징(이목구비)을 추출하고, 추출된 특징정보를 이용하여 기와 유사한 특징정보를 가지는 캐리커처 이미지를 검색하여 매핑시키는 시스템이다. 캐리커처 생성 시스템에 얼굴 특징정보 추출은 색상과 모양에 대한 정보를 이용한다. 본 논문은 캐리커처생성을 위한 인물 사진을 세그멘테이션 처리하여 부분 영역 특징정보를 추출하는데 그 목적이 있다. 이때 사용하는 이목구비의 특징정보를 위해 수직, 수평의 히스토그램이 주요하게 사용된다. 또한 인물 사진에서 위치정보를 이용하여 얼굴내의 이목구비를 확인하고, 추출하므로 정확한 정보를 이용할 수 있다.

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.47-58
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• 2018

In this paper, we propose a method for skin condition analysis using a camera module embedded in a smartphone without a separate skin diagnosis device. The type of skin disease detected in facial image taken by smartphone is acne, pigmentation, blemish and flush. Face features and regions were detected using Haar features, and skin regions were detected using YCbCr and HSV color models. Acne and flush were extracted by setting the range of a component image hue, and pigmentation was calculated by calculating the factor between the minimum and maximum value of the corresponding skin pixel in the component image R. Blemish was detected on the basis of adaptive thresholds in gray scale level images. As a result of the experiment, the proposed skin condition analysis showed that skin diseases of acne, pigmentation, blemish and flush were effectively detected.

• Archives of Craniofacial Surgery
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• v.20 no.4
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• pp.265-269
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• 2019

Congenital hypoplasia of the depressor anguli oris muscle is a rare cause of asymmetrical crying facies in newborns. The clinical manifestations range from mild to severe asymmetry and may persist up to adulthood. In the current case, the patient did not exhibit other congenital anomalies or paralysis of other branches of the facial nerve. This adult patient presented with severe asymmetrical lower lip deformity during full mouth opening since birth. A chromosomal study for the detection of 22q gene deletion yielded negative results. The electromyography findings of the lower lip were insignificant. Depressor labii inferioris muscle resection was not effective, but bidirectional (horizontal and vertical) fascia lata grafting improved the aesthetic appearance of the asymmetrical lower lip. The patient showed improved lower lip symmetry during full mouth opening at 1 year after the surgery. Therefore, the details of this rare case are reported herein.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.21-28
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• 2022

People differ greatly in their capacity to persist in the face of challenges. Despite significant research, relatively little is known about cognitive factors that might be involved in perseverance. Building upon human threat-management mechanism, we predicted that perseverant people would be characterized by reduced sensitivity (i.e., longer detection latency) to threat cues. Our data from 5,898 job applicants showed that highly perseverant individuals required more time to correctly identify anger in faces, regardless of stimulus type (dynamic or static computer-morphed faces). Such individual differences were not observed in response to other facial expressions (happiness, sadness), and the effect was independent of gender, dispositional anxiety, or conscientiousness. Discussions were centered on the potential role of threat sensitivity in effortful pursuit of goals.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.121-126
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• 2004

An efficient multi face detection technique is proposed based on hierarchical context-free attention operators in which multiple faces are efficiently detected from a noisy and complex background. A noise-tolerant generalized symmetry transform (NTSGT) is applied hierarchically, as a context free attention operator, to the input pyramidal image for the high speed global location of the regions of face candidates (ROFCs) with a single mask. For the face verification, local NTGST is applied within each ROFC to confirm the existence of the detailed facial features. First, by globally applying NTGST which introduces the average pyramid method and focusing to the input image with complex background, ROFCs with recognizable resolution are detected robustly. Morphological operations are applied only to the each detected ROFCs to emphasize the facial features like eyes and lips. Then, eyes are detected by locally appling NTGST to the ROFCs and only faces are detected by verifying the existence of the geometrical features of the faces relatively to the location of eyes. The experimental results show that the proposed method can efficiently detect multiple faces from a noisy or complex background with 93.5% detection rate.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.34-43
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• 2008

This paper presents a system for recognizing sunglasses and a mask of an ATM (Automatic Teller Machine) user. The proposed system extracts firstly facial contour, then from this extraction results it estimates the regions of eyes and mouth. Finally, it recognizes sunglasses and a mouth using Histogram Indexing based on those regions. We adopt a face shape model to be able to extract facial contour and to estimate the regions of eyes and mouth when those regions are occluded by sunglasses and a mask. To improve the fitting accuracy of the shame model, we adopt 2-step face detection method and conduct fitting several times by varying the initial position of the model instance. To achieve a good performance of the face detection method based on a background model, we enable the system to automatically update the background model. In experiment, we present some experiments on setting parameters of the system with images taken from in our laboratory, and demonstrate the results of recognizing sunglasses and a mask.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.99-112
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• 2015

Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.4 s.310
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• pp.58-66
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• 2006

In this paper, we apply DCM(Dilation of Color and Motion information) mask and Active Contour Models(Snakes) to extract facial outline in moving pictures with complex background. First, we propose DCM mask which is made by applying morphology dilation and AND operation to combine facial color and motion information, and use this mask to detect facial region without complex background and to remove noise in image energy. Also, initial curves are automatically set according to rotational degree estimated with geometric ratio of facial elements to overcome the demerit of Active Contour Models which is sensitive to initial curves. And edge intensity and brightness are both used as image energy of snakes to extract contour at parts with weak edges. For experiments, we acquired total 480 frames with various head-poses of sixteen persons with both eyes shown by taking pictures in inner space and also by capturing broadcasting images. As a result, it showed that more elaborate facial contour is extracted at average processing time of 0.28 seconds when using interpolated initial curves according to facial rotation degree and using combined image energy of edge intensity and brightness.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.132-142
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• 2021

The purpose of this study is to present an effective methodology that can measure heart rate, heart rate variability, oxygen saturation, respiration rate, mental stress level, and blood pressure using mobile front camera that can be accessed most in real life. Face recognition was performed in real-time using Blaze Face to acquire facial image data, and the forehead was designated as ROI (Region Of Interest) using feature points of the eyes, nose, and mouth, and ears. Representative values for each channel of the ROI were generated and aligned on the time axis to measure vital signs. The vital signs measurement method was based on Fourier transform, and noise was removed and filtered according to the desired vital signs to increase the accuracy of the measurement. To verify the results, vital signs measured using facial image data were compared with pulse oximeter contact sensor, and TI non-contact sensor. As a result of this work, the possibility of extracting a total of six vital signs (heart rate, heart rate variability, oxygen saturation, respiratory rate, stress, and blood pressure) was confirmed through facial images.