• Title/Summary/Keyword: Eye region detection

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Robust Pupil Detection using Rank Order Filter and Cross-Correlation (Rank Order Filter와 상호상관을 이용한 강인한 눈동자 검출)

  • Jang, Kyung-Shik;Park, Sung-Dae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.7
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    • pp.1564-1570
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    • 2013
  • In this paper, we propose a robust pupil detection method using rank order filter and cross-correlation. Potential pupil candidates are detected using rank order filter. Eye region is binarized using variable threshold to find eyebrow, and pupil candidates at the eyebrow are removed. The positions of pupil candidates are corrected, the pupil candidates are grouped into pairs based on geometric constraints. A similarity measure is obtained for two eye of each pair using cross-correlation, we select a pair with the largest similarity measure as a final pupil. The experiments have been performed for 500 images of the BioID face database. The results show that it achieves the high detection rate of 96.8% and improves about 11.6% than existing method.

Skin Color Based Facial Features Extraction

  • Alom, Md. Zahangir;Lee, Hyo Jong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2011.11a
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    • pp.351-354
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    • 2011
  • This paper discusses on facial features extraction based on proposed skin color model. Different parts of face from input image are segmented based on skin color model. Moreover, this paper also discusses on concept to detect the eye and mouth position on face. A height and width ratio (${\delta}=1.1618$) based technique is also proposed to accurate detection of face region from the segmented image. Finally, we have cropped the desired part of the face. This exactly exacted face part is useful for face recognition and detection, facial feature analysis and expression analysis. Experimental results of propose method shows that the proposed method is robust and accurate.

Region-based Face Makeup using two example face images (두 가지 예제 이미지를 이용한 얼굴 영역 별 메이크업)

  • Lee, Jae-Yoon;Kang, Hang-Bong
    • Journal of Korea Multimedia Society
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    • v.18 no.9
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    • pp.1019-1026
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    • 2015
  • In this paper, we propose a new method of eye, face, and lip makeup techniques on the target face image from several makeup examples without losing detail features such as eyelids, eyebrows, hair. After detection of the feature layer for the skin, we applied our makeup techniques to the target face by using a blending technique. We used a cartoon rendering using bilateral filter. In order to smoothly makeup the target face, we created two Gaussian Weight maps for natural skin makeup effects. Our method did not need to perform complex operations, so the makeup results are so natural. Our experimental results show good performances in various makeups.

Development of Pose-Invariant Face Recognition System for Mobile Robot Applications

  • Lee, Tai-Gun;Park, Sung-Kee;Kim, Mun-Sang;Park, Mig-Non
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.783-788
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    • 2003
  • In this paper, we present a new approach to detect and recognize human face in the image from vision camera equipped on the mobile robot platform. Due to the mobility of camera platform, obtained facial image is small and pose-various. For this condition, new algorithm should cope with these constraints and can detect and recognize face in nearly real time. In detection step, ‘coarse to fine’ detection strategy is used. Firstly, region boundary including face is roughly located by dual ellipse templates of facial color and on this region, the locations of three main facial features- two eyes and mouth-are estimated. For this, simplified facial feature maps using characteristic chrominance are made out and candidate pixels are segmented as eye or mouth pixels group. These candidate facial features are verified whether the length and orientation of feature pairs are suitable for face geometry. In recognition step, pseudo-convex hull area of gray face image is defined which area includes feature triangle connecting two eyes and mouth. And random lattice line set are composed and laid on this convex hull area, and then 2D appearance of this area is represented. From these procedures, facial information of detected face is obtained and face DB images are similarly processed for each person class. Based on facial information of these areas, distance measure of match of lattice lines is calculated and face image is recognized using this measure as a classifier. This proposed detection and recognition algorithms overcome the constraints of previous approach [15], make real-time face detection and recognition possible, and guarantee the correct recognition irregardless of some pose variation of face. The usefulness at mobile robot application is demonstrated.

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Robust Real-time Face Detection Scheme on Various illumination Conditions (다양한 조명 환경에 강인한 실시간 얼굴확인 기법)

  • Kim, Soo-Hyun;Han, Young-Joon;Cha, Hyung-Tai;Hahn, Hern-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.7
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    • pp.821-829
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    • 2004
  • A face recognition has been used for verifying and authorizing valid users, but its applications have been restricted according to lighting conditions. In order to minimizing the restricted conditions, this paper proposes a new algorithm of detecting the face from the input image obtained under the irregular lighting condition. First, the proposed algorithm extracts an edge difference image from the input image where a skin color and a face contour are disappeared due to the background color or the lighting direction. In the next step, it extracts a face region using the histogram of the edge difference image and the intensity information. Using the intensity information, the face region is divided into the horizontal regions with feasible facial features. The each of horizontal regions is classified as three groups with the facial features(including eye, nose, and mouth) and the facial features are extracted using empirical properties of the facial features. Only when the facial features satisfy their topological rules, the face region is considered as a face. It has been proved by the experiments that the proposed algorithm can detect faces even when the large portion of face contour is lost due to the inadequate lighting condition or the image background color is similar to the skin color.

Development of Real-Time Vision-based Eye-tracker System for Head Mounted Display (영상정보를 이용한 HMD용 실시간 아이트랙커 시스템)

  • Roh, Eun-Jung;Hong, Jin-Sung;Bang, Hyo-Choong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.35 no.6
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    • pp.539-547
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    • 2007
  • In this paper, development and tests of a real-time eye-tracker system are discussed. The tracker system tracks a user's gaze point through movement of eyes by means of vision-based pupil detection. The vision-based method has an advantage of detecting the exact positions of user's eyes. An infrared camera and a LED are used to acquire a user's pupil image and to extract pupil region, which was hard to extract with software only, from the obtained image, respectively. We develop a pupil-tracking algorithm with Kalman filter and grab the pupil images by using DSP(Digital Signal Processing) system for real-time image processing technique. The real-time eye-tracker system tracks the movements of user's pupils to project their gaze point onto a background image.

Robust Extraction of Facial Features under Illumination Variations (조명 변화에 견고한 얼굴 특징 추출)

  • Jung Sung-Tae
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.6 s.38
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    • pp.1-8
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    • 2005
  • Facial analysis is used in many applications like face recognition systems, human-computer interface through head movements or facial expressions, model based coding, or virtual reality. In all these applications a very precise extraction of facial feature points are necessary. In this paper we presents a method for automatic extraction of the facial features Points such as mouth corners, eye corners, eyebrow corners. First, face region is detected by AdaBoost-based object detection algorithm. Then a combination of three kinds of feature energy for facial features are computed; valley energy, intensity energy and edge energy. After feature area are detected by searching horizontal rectangles which has high feature energy. Finally, a corner detection algorithm is applied on the end region of each feature area. Because we integrate three feature energy and the suggested estimation method for valley energy and intensity energy are adaptive to the illumination change, the proposed feature extraction method is robust under various conditions.

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Development of a Loop-Mediated Isothermal Amplification Assay for Rapid Detection of Nocardia salmonicida, the Causative Agent of Nocardiosis in Fish

  • Xia, Liqun;Zhang, Honglian;Lu, Yishan;Cai, Jia;Wang, Bei;Jian, Jichang
    • Journal of Microbiology and Biotechnology
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    • v.25 no.3
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    • pp.321-327
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    • 2015
  • Nocardia salmonicida is one of the main pathogens of fish nocardiosis. The purpose of this study was to build a loop-mediated isothermal amplification (LAMP) method for the rapid and sensitive detection of N. salmonicida. A set of four primers were designed from the 16S-23S rRNA intergenic spacer region of N. salmonicida, and conditions for LAMP were optimized as incubating all the reagents for 60 min at 64℃. LAMP products were judged with agar gel electrophoresis as well as with the naked eye after the addition of SYBR Green I. Results showed the sensitivity of the LAMP assay was 1.68 × 103 CFU/ml (16.8 CFU per reaction) and 10-fold higher than that of PCR. The LAMP method was also effectively applied to detect N. salmonicida in diseased fish samples, and it may potentially facilitate the surveillance and early diagnosis of fish nocardiosis.

Face and Facial Feature Detection under Pose Variation of User Face for Human-Robot Interaction (인간-로봇 상호작용을 위한 자세가 변하는 사용자 얼굴검출 및 얼굴요소 위치추정)

  • Park Sung-Kee;Park Mignon;Lee Taigun
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.1
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    • pp.50-57
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    • 2005
  • We present a simple and effective method of face and facial feature detection under pose variation of user face in complex background for the human-robot interaction. Our approach is a flexible method that can be performed in both color and gray facial image and is also feasible for detecting facial features in quasi real-time. Based on the characteristics of the intensity of neighborhood area of facial features, new directional template for facial feature is defined. From applying this template to input facial image, novel edge-like blob map (EBM) with multiple intensity strengths is constructed. Regardless of color information of input image, using this map and conditions for facial characteristics, we show that the locations of face and its features - i.e., two eyes and a mouth-can be successfully estimated. Without the information of facial area boundary, final candidate face region is determined by both obtained locations of facial features and weighted correlation values with standard facial templates. Experimental results from many color images and well-known gray level face database images authorize the usefulness of proposed algorithm.

Machine's Determination of Main Color and Imbalance in a Drawing for Art Psychotherapy (그림진단을 위한 주제색 및 불균형 판단의 자동화)

  • Bae Jun;Kim Jae Min;Kim Seong-in
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.2
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    • pp.119-129
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    • 2006
  • Art psychotherapy is widely accepted as an effective tool for diagnosis and treatment of psychological disorders. Important factors for art psychotherapy diagnosis, based on the projection theory that the world of the inner mind appears in drawings, include main color and imbalance of a drawing. This paper develops a system for a machine to determine the main color and the imbalance of a drawing by color recognition and edge detection. Our proposed color recognition procedure adopts NBS(National Bureau of Standards) distance between colors in HVC(Hue, Value, Chroma) color space which is most similar to the human eye's color perception. Our edge detection procedure applies blurring, clustering and transformation to a standard color in a series. Our system considers the numbers of pixels and clusters for each color as a criterion for main color and the frequency of edge coordinates for each region for imbalance. The proposed machine procedure, verified through case studies, can help overcome the subjectivity, ambiguity and uncertainty in human decision involved in art psychotherapy.