• 제목/요약/키워드: Skin recognition

검색결과 314건 처리시간 0.031초

YCbCr 색 좌표계의 모든 요소를 고려한 3-channel 피부 검출 알고리즘 (Three channel Skin-Detection Algorithm for considering all constituent in YCbCr color space)

  • 신선미;임정욱;장원우;곽부동;강봉순
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2007년도 추계종합학술대회
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    • pp.127-130
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    • 2007
  • 화상 통신과 보안 시스템에서 얼굴 인식을 위한 얼굴영역을 검출하는 연구가 대두되며, 이러한 연구의 전 처리 단계로써 YCbCr 색 좌표계에서 색 정보를 이용하여 피부영역만을 검출하는 알고리즘을 제안한다. CbCr 색 정보를 이용한 기존의 피부 영역 검출 알고리즘의 경우, 실외나 카메라 풀래시를 사용하였을 때 반사광에 의해 밝게 나타난 피부 영역에서 검출 손상이 발생하는 문제점이 나타났다. 따라서 본 논문에서는 어떠한 환경에서도 피부색만을 정확하게 검출하기 위해 기존의 알고리즘을 개선하여 Cb, Cr 뿐만 아니라 Y(Luminance) 값까지 모두 고려한 3-channel 구조의 피부 검출 시스템을 제안한다.

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Non-parametric Density Estimation with Application to Face Tracking on Mobile Robot

  • Feng, Xiongfeng;Kubik, K.Bogunia
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.49.1-49
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    • 2001
  • The skin color model is a very important concept in face detection, face recognition and face tracking. Usually, this model is obtained by estimating a probability density function of skin color distribution. In many cases, it is assumed that the underlying density function follows a Gaussian distribution. In this paper, a new method for non-parametric estimation of the probability density function, by using feed-forward neural network, is used to estimate the underlying skin color model. By using this method, the resulting skin color model is better than the Gaussian estimation and substantially approaches the real distribution. Applications to face detection and face ...

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웹캠을 이용한 손동작 인식 방법 (A Hand Gesture Recognition Scheme using WebCAM)

  • 김건우;이원주;전창호
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2008년도 하계종합학술대회
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    • pp.619-620
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    • 2008
  • In this paper, we propose a new hand gesture recognition scheme using hand poses captured from a web camera. The key idea of this scheme is to extract skin color from the background-subtracted image. To extract skin color, in the first phase, we subtract background by repeatedly comparing the stored initial frame with next frames. And then we eliminate noise using dynamic table. In the second phase, we exactly recognize hand gesture by extracting skin color from ${YC_b}{C_r}$ color region.

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디스플레이 현황과 발전방향 -실감 및 스킨 기기로의 확대 (Display Technologies for Immersive Devices and Electronic Skin)

  • 박영준
    • 전자통신동향분석
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    • 제34권2호
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    • pp.10-18
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    • 2019
  • Since the introduction of CRT(Cathode Ray Tube) in the 1950s, display technologies have been developed continuously. Flat panel displays such as PDP(Plasma Display Panel) and LCD(Liquid Crystal Display) were commercialized in the late 1990s, and OLED(Organic Light Emitting Diodes) and Micro-LED(Micro-Light Emitting Diodes) are now being developed and are becoming widespread. In the future, we expect to develop ultra-realistic, flexible, embedded sensor displays. Ultra-realistic display can be applied to AR/VR(Augmented Reality/Virtual Reality) devices and spatial light modulators for holography. The sensor-embedded display can be applied to robots; electronic skin; and security devices, including iris recognition sensors, fingerprint recognition sensors, and tactile sensors. AR/VR technology must be developed to meet technical requirements such as viewing angle, resolution, and refresh rate. Holography requires optical modulation technology that can significantly improve resolution, viewing angle, and modulation method to enable wide-view and high-quality hologram stereoscopic images. For electronic skin, stable mass production technology, large-area arrays, and system integration technologies should be developed.

Half-Against-Half Multi-class SVM Classify Physiological Response-based Emotion Recognition

  • ;고광은;박승민;심귀보
    • 한국지능시스템학회논문지
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    • 제23권3호
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    • pp.262-267
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    • 2013
  • The recognition of human emotional state is one of the most important components for efficient human-human and human- computer interaction. In this paper, four emotions such as fear, disgust, joy, and neutral was a main problem of classifying emotion recognition and an approach of visual-stimuli for eliciting emotion based on physiological signals of skin conductance (SC), skin temperature (SKT), and blood volume pulse (BVP) was used to design the experiment. In order to reach the goal of solving this problem, half-against-half (HAH) multi-class support vector machine (SVM) with Gaussian radial basis function (RBF) kernel was proposed showing the effective techniques to improve the accuracy rate of emotion classification. The experimental results proved that the proposed was an efficient method for solving the emotion recognition problems with the accuracy rate of 90% of neutral, 86.67% of joy, 85% of disgust, and 80% of fear.

The Association between Skin Type and Skin Care Behavior and Stress Perception during COVID-19 Pandemic

  • Tae-Oim KIM;Ki-Han KWON
    • 산경연구논집
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    • 제14권4호
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    • pp.33-46
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    • 2023
  • Purpose: During the coronavirus disease-19 (COVID-19) outbreak, mask-wearing is required to protect against and limit the spread of infection, but it can directly affect skin problems. Change in skin condition might be related to mental health. This study explored the association between skin conditions and behavior of skin cares and stress levels during the Covid-19pandemics. Research design, data and methodology: A survey was conducted on 516 adults who were aware of damaged skin due to continuous wearing of masks for a long time during the COVID-19 Pandemic. The study included 164 men and 352 women in the Republic of Korea. Results: Skin conditions and behavior of skin cares associated with stress perceptions. A multiple linear regression model was used adjusting for potential confounder. Conclusion: Since management so far in the COVID-19 Pandemic can cause skin concerns and change the original skin type, it is necessary to redefine and improve the use of skin care, face-washing methods, and functional cosmetics. People with high and low interest in skin type recognition and management were evenly identified, and it was confirmed that stress awareness decreases as awareness of skin care attitude increases.

다층 신경망과 피부색 모델을 이용한 피부 영역 검출 (Skin Region Extraction Using Multi-Layer Neural Network and Skin-Color Model)

  • 박성욱;박종욱
    • 한국산업정보학회논문지
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    • 제16권2호
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    • pp.31-38
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    • 2011
  • 피부색은 자동화된 얼굴 인식을 위한 매우 중요한 정보 중의 하나이다. 본 논문에서는 다층 신경망(Multi-Layer Perceptron)을 이용한 피부 영역 검출 기법을 제안하였다. 제안된 방법은 적응적 조명 보정 기법을 통해 피부색 영역의 검출 성능을 개선하였고, 전처리 필터를 적용하여 피부색이 아닌 영역을 먼저 제거시킴으로써 처리 속도를 향상시켰다. 제안된 방법의 실험 결과 기존의 방법과 비교하여 보다 우수한 검출 결과를 나타냈으며, 처리 속도 또한 약 31~49% 향상시킬 수 있었다.

Automatic Face Identification System Using Adaptive Face Region Detection and Facial Feature Vector Classification

  • Kim, Jung-Hoon;Do, Kyeong-Hoon;Lee, Eung-Joo
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -2
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    • pp.1252-1255
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    • 2002
  • In this paper, face recognition algorithm, by using skin color information of HSI color coordinate collected from face images, elliptical mask, fratures of face including eyes, nose and mouth, and geometrical feature vectors of face and facial angles, is proposed. The proposed algorithm improved face region extraction efficacy by using HSI information relatively similar to human's visual system along with color tone information about skin colors of face, elliptical mask and intensity information. Moreover, it improved face recognition efficacy with using feature information of eyes, nose and mouth, and Θ1(ACRED), Θ2(AMRED) and Θ 3(ANRED), which are geometrical face angles of face. In the proposed algorithm, it enables exact face reading by using color tone information, elliptical mask, brightness information and structural characteristic angle together, not like using only brightness information in existing algorithm. Moreover, it uses structural related value of characteristics and certain vectors together for the recognition method.

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얼굴 특징 변화에 따른 휴먼 감성 인식 (Human Emotion Recognition based on Variance of Facial Features)

  • 이용환;김영섭
    • 반도체디스플레이기술학회지
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    • 제16권4호
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    • pp.79-85
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    • 2017
  • Understanding of human emotion has a high importance in interaction between human and machine communications systems. The most expressive and valuable way to extract and recognize the human's emotion is by facial expression analysis. This paper presents and implements an automatic extraction and recognition scheme of facial expression and emotion through still image. This method has three main steps to recognize the facial emotion: (1) Detection of facial areas with skin-color method and feature maps, (2) Creation of the Bezier curve on eyemap and mouthmap, and (3) Classification and distinguish the emotion of characteristic with Hausdorff distance. To estimate the performance of the implemented system, we evaluate a success-ratio with emotional face image database, which is commonly used in the field of facial analysis. The experimental result shows average 76.1% of success to classify and distinguish the facial expression and emotion.

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아시아인의 얼굴색 변화와 인지도간 상관성 비교 : 한국인, 인도네시아인, 베트남인 (Comparison Between Face Color Change and Its Recognition Difference on Asian: Korean, Indonesian and Vietnamian)

  • 정유철;이명렬;김은주;조준철;이해광
    • 대한화장품학회지
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    • 제39권4호
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    • pp.323-327
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    • 2013
  • 수분량, 유분량, 피부밝기, pH 등 피부 특성을 나타내는 지표들은 환경적, 유전적 요소에 따라 다르게 나타난다. 하지만 이는 절대적인 피부 특성을 나타내는 것으로 사람들이 느끼는 감성적인 피부 특성과는 차이가 있다. 이를 반영하듯 최근 임상 연구들은 절대적인 피부 변화를 통한 사람들의 인지 변화에 관한 연구들이 주를 이루고 있다. 본 연구에서는 아시아인을 대상으로 국가별로 절대적인 피부색의 차이 뿐 아니라 실제 피부색의 변화에 따라 본인들이 인지하는 피부 밝기에도 차이가 있는지를 규명하고자 하였다. 아시아 3개국 총 410명의 피험자들이 본 연구에 참여하였으며 설문을 통해 본인들이 생각하는 피부밝기를 3단계로 구분하여 응답하고 본인이 생각하는 피부 밝기 변화에 따라 실제 피부색은 어떤 양상으로 변화하는지를 분석하였다. 국적에 관계 없이 모든 참가자들이 공통적으로 피부색이 밝다고 느낄수록 실제 피부 밝기는 증가하는 양상을 보였지만 절대적인 피부색과 피부가 밝다고 느끼는 정도는 차이가 있었다. 게다가, 피부 붉은기와 노란기의 변화도 국가별로 다른 양상을 보였다. 결론적으로, 본 연구 결과에 근거하여 판단 할 때 본인들의 피부 밝기를 인지하는 요소는 절대적인 피부 밝기가 아닌 국가별로 다른 기준이 적용된다는 것을 확인할 수 있었다.