• Title/Summary/Keyword: Lip detection

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A Method of Eye and Lip Region Detection using Faster R-CNN in Face Image (초고속 R-CNN을 이용한 얼굴영상에서 눈 및 입술영역 검출방법)

  • Lee, Jeong-Hwan
    • Journal of the Korea Convergence Society
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    • v.9 no.8
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    • pp.1-8
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    • 2018
  • In the field of biometric security such as face and iris recognition, it is essential to extract facial features such as eyes and lips. In this paper, we have studied a method of detecting eye and lip region in face image using faster R-CNN. The faster R-CNN is an object detection method using deep running and is well known to have superior performance compared to the conventional feature-based method. In this paper, feature maps are extracted by applying convolution, linear rectification process, and max pooling process to facial images in order. The RPN(region proposal network) is learned using the feature map to detect the region proposal. Then, eye and lip detector are learned by using the region proposal and feature map. In order to examine the performance of the proposed method, we experimented with 800 face images of Korean men and women. We used 480 images for the learning phase and 320 images for the test one. Computer simulation showed that the average precision of eye and lip region detection for 50 epoch cases is 97.7% and 91.0%, respectively.

Adaptive Background Modeling Considering Stationary Object and Object Detection Technique based on Multiple Gaussian Distribution

  • Jeong, Jongmyeon;Choi, Jiyun
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.11
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    • pp.51-57
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    • 2018
  • In this paper, we studied about the extraction of the parameter and implementation of speechreading system to recognize the Korean 8 vowel. Face features are detected by amplifying, reducing the image value and making a comparison between the image value which is represented for various value in various color space. The eyes position, the nose position, the inner boundary of lip, the outer boundary of upper lip and the outer line of the tooth is found to the feature and using the analysis the area of inner lip, the hight and width of inner lip, the outer line length of the tooth rate about a inner mouth area and the distance between the nose and outer boundary of upper lip are used for the parameter. 2400 data are gathered and analyzed. Based on this analysis, the neural net is constructed and the recognition experiments are performed. In the experiment, 5 normal persons were sampled. The observational error between samples was corrected using normalization method. The experiment show very encouraging result about the usefulness of the parameter.

Lip Region Extraction by Gaussian Classifier (가우스 분류기를 이용한 입술영역 추출)

  • Kim, Jeong Yeop
    • Journal of Korea Multimedia Society
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    • v.20 no.2
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    • pp.108-114
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    • 2017
  • Lip reading is a field of image processing to assist the process of sound recognition. In some environment, the capture of sound signal usually has significant noise and therefore, the recognition rate of sound signal decreases. Lip reading can be a good feature for the increase of recognition rates. Conventional lip extraction methods have been proposed widely. Maia et. al. proposed a method by the sum of Cr and Cb. However, there are two problems as follows: the point with maximum saturation is not always regarded as lips region and the inner part of lips such as oral cavity and teeth can be classified as lips. To solve these problems, this paper proposes a method which adopts the histogram-based classifier for the extraction of lips region. The proposed method consists of two stages, learning and test. The amount of computation is minimized because this method has no color conversion. The performance of proposed method gives 66.8% of detection rate compared to 28% of conventional ones.

Pupil and Lip Detection using Shape and Weighted Vector based on Shape (형태와 가중치 벡터를 이용한 눈동자와 입술 검출)

  • Jang, kyung-Shik
    • Journal of KIISE:Software and Applications
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    • v.29 no.5
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    • pp.311-318
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    • 2002
  • In this paper, we propose an efficient method for recognizing pupils and lip in a human face. Pupils are detected by a cost function, which uses features based on the eye's shape and a relation between pupil and eyebrow. The inner boundary of lip is detected by weighted vectors based on lip's shape and on the difference of gray level between lip and face skin. These vectors extract four feature points of lip : the top of the upper lip, the bottom of the lower lip, and the two corners. The experiments have been performed for many images and show very encouraging result.

Lip Shape Representation and Lip Boundary Detection Using Mixture Model of Shape (형태계수의 Mixture Model을 이용한 입술 형태 표현과 입술 경계선 추출)

  • Jang Kyung Shik;Lee Imgeun
    • Journal of Korea Multimedia Society
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    • v.7 no.11
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    • pp.1531-1539
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    • 2004
  • In this paper, we propose an efficient method for locating human lips. Based on Point Distribution Model and Principle Component Analysis, a lip shape model is built. Lip boundary model is represented based on the concatenated gray level distribution model. We calculate the distribution of shape parameters using Gaussian mixture. The problem to locate lip is simplified as the minimization problem of matching object function. The Down Hill Simplex Algorithm is used for the minimization with Gaussian Mixture for setting initial condition and refining estimate of lip shape parameter, which can refrain iteration from converging to local minima. The experiments have been performed for many images, and show very encouraging result.

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IMMUNOHISTOCHEMICAL DETECTION OF GROWTH FACTORS AND EXTRACELLULAR MATRIX PROTEINS IN THE DEGENERATING TISSUES OF PRE-AND POSTNATAL HUMAN CLEFT LIP AND PALATE (태생 및 생후 구순.구개열에 나타나는 조직변성에 대한 성장인자와 세포외 기질 단백의 면역조직화학적 연구)

  • Min, Bong-Gi;Lee, Suk-Keun;Park, Young-Wook
    • Journal of the Korean Association of Oral and Maxillofacial Surgeons
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    • v.28 no.6
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    • pp.421-433
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    • 2002
  • In order to elucidate the pathogenesis of cleft lip and palate, first of all, it is necessary to understand the developmental mechanisms of growth factors and extracellular matrix proteins in the tissues of cleft lip and palate. We have performed immunohistochemical studies on human cleft lip and palate tissues to elucidate the pathogenetic implications of cleft lip and palate. 16 specimens from postnatal human cleft lip and palate subjects and 17 specimens from autopsy of prenatal human cleft lip and palate were fixed in 10% buffered formalin, embedded in paraffin. The sections were routinely stained by hematoxylin and eosin, also stained by PAS, and followed by immunohistochemical stainings using the antiseras of growth factors and extracellular matrix proteins such as PCNA, S-100, c-erb-B2, MMP-3, MMP-10, HSP-70, transglutaninase-C, E-cadherin, VEGF, vWF. Both the prenatal and postnatal specimens of cleft lip and palate showed dysplastic proliferation of the basal cell layer, increased infiltration of melanocytes into mucosal epithelium, sebaceous gland hyperplasia ingrowing into the muscular tissue of lip and palate, and fatty infiltration into the submucosal deep connective tissue. The strong reactions of MMP-3 and HSP-70 were detected in the tissues of cleft lip and palate, especially increased in degenerating muscle bundles, while the immunostainings of PCNA and c-erb-B2 were weakly positive in the tissues of cleft lip and palate. These data suggest that the retrogressive tissue degeneration around the cleft areas persistently exist during the prenatal and postnatal period after cleft formation, and the sebaceous gland hyperplasia and fatty infiltration with the intense expression of MMP-3 and HSP-70 is closely related to the muscular degeneration around the cleft area.

Speech Activity Detection using Lip Movement Image Signals (입술 움직임 영상 선호를 이용한 음성 구간 검출)

  • Kim, Eung-Kyeu
    • Journal of the Institute of Convergence Signal Processing
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    • v.11 no.4
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    • pp.289-297
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    • 2010
  • In this paper, A method to prevent the external acoustic noise from being misrecognized as the speech recognition object is presented in the speech activity detection process for the speech recognition. Also this paper confirmed besides the acoustic energy to the lip movement image signals. First of all, the successive images are obtained through the image camera for personal computer and the lip movement whether or not is discriminated. The next, the lip movement image signal data is stored in the shared memory and shares with the speech recognition process. In the mean time, the acoustic energy whether or not by the utterance of a speaker is verified by confirming data stored in the shared memory in the speech activity detection process which is the preprocess phase of the speech recognition. Finally, as a experimental result of linking the speech recognition processor and the image processor, it is confirmed to be normal progression to the output of the speech recognition result if face to the image camera and speak. On the other hand, it is confirmed not to the output the result of the speech recognition if does not face to the image camera and speak. Also, the initial feature values under off-line are replaced by them. Similarly, the initial template image captured while off-line is replaced with a template image captured under on-line, so the discrimination of the lip movement image tracking is raised. An image processing test bed was implemented to confirm the lip movement image tracking process visually and to analyze the related parameters on a real-time basis. As a result of linking the speech and image processing system, the interworking rate shows 99.3% in the various illumination environments.

Lip Detection Algorithm Using Color Clustering (색상 군집화를 이용한 입술탐지 알고리즘)

  • Jeong, Jongmyeon;Choi, Jiyun;Seo, Ji Hyuk;Lee, Se Jun
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2012.07a
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    • pp.277-278
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    • 2012
  • 본 논문에서는 색상 군집화를 이용한 입술탐지 알고리즘을 제안한다. 이를 위해 이미 많이 알려져 있는 AdaBoost를 이용한 얼굴탐지를 수행한다. 탐지된 얼굴영역에 Lab 컬러시스템을 적용 시킨 후 입술픽셀의 특징에 따른 색상 마커를 사용하여 피부영역을 추출한다. 추출된 피부영역에 대하여 K-means 색상 군집화를 통해 입술영역을 추출한다. 그리고 실험을 통해 입술탐지 결과를 확인하였다.

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Congenital unilateral hypoplasia of depressor anguli oris muscle in adult

  • Oh, Suk Joon
    • 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.

Analysis of CIELuv Color feature for the Segmentation of the Lip Region (입술영역 분할을 위한 CIELuv 칼라 특징 분석)

  • Kim, Jeong Yeop
    • Journal of Korea Multimedia Society
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    • v.22 no.1
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    • pp.27-34
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    • 2019
  • In this paper, a new type of lip feature is proposed as distance metric in CIELUV color system. The performance of the proposed feature was tested on face image database, Helen dataset from University of Illinois. The test processes consists of three steps. The first step is feature extraction and second step is principal component analysis for the optimal projection of a feature vector. The final step is Otsu's threshold for a two-class problem. The performance of the proposed feature was better than conventional features. Performance metrics for the evaluation are OverLap and Segmentation Error. Best performance for the proposed feature was OverLap of 65% and 59 % of segmentation error. Conventional methods shows 80~95% for OverLap and 5~15% of segmentation error usually. In conventional cases, the face database is well calibrated and adjusted with the same background and illumination for the scene. The Helen dataset used in this paper is not calibrated or adjusted at all. These images are gathered from internet and therefore, there are no calibration and adjustment.