• Title/Summary/Keyword: Facial Region

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Preoperative Evaluation of the Facial Artery Using Facial Angio Computed Tomography (전산화단층촬영 혈관조영술을 이용한 얼굴동맥의 수술 전 평가)

  • Kim, Joo-Hak;Kang, Nak-Heon;Lee, In-Ho;Seo, Young-Joon;Yang, Ho-Jik;Song, Seung-Han;Oh, Sang-Ha
    • Archives of Plastic Surgery
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    • v.38 no.6
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    • pp.719-724
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    • 2011
  • Purpose: Previous studies of the facial artery have shown significant anatomical variability in this region. The vascular anatomy of the region is considered unreliable in predicting the ideal pedicle. Preoperative imaging has been suggested as a means of improving preoperative awareness, with Doppler ultrasound as useful tools. Multi-detector row angiographic computed tomography (angio CT) is a significant improvement, providing noninvasive operator-independent details of the vascular anatomy. This tool was used to perform an $in$ $vivo$ anatomical study of the facial artery, demonstrating the usefulness of facial angio CT in planning the facial reconstruction. Methods: Eleven consecutive patients underwent facial angio CT of the facial vasculature with the anatomical details of the facial artery assessed. Results: Facial angio CT could demonstrate the size and course of the facial vasculature, particularly the facial artery. Conclusion: The vascular anatomy of the facial artery is highly variable, and thus there is a role for preoperative imaging. Facial angio CT can demonstrate cases where there is an aberrant or non-preferred anatomy, or select the method of a facial reconstruction.

Facial Region Segmentation using Watershed Algorithm based on Depth Information (깊이정보 기반 Watershed 알고리즘을 이용한 얼굴영역 분할)

  • Kim, Jang-Won
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.4 no.4
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    • pp.225-230
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    • 2011
  • In this paper, we propose the segmentation method for detecting the facial region by using watershed based on depth information and merge algorithm. The method consists of three steps: watershed segmentation, seed region detection, and merge. The input color image is segmented into the small uniform regions by watershed. The facial region can be detected by merging the uniform regions with chromaticity and edge constraints. The problem in the existing method using only chromaticity or edge can solved by the proposed method. The computer simulation is performed to evaluate the performance of the proposed method. The simulation results shows that the proposed method is superior to segmentation facial region.

Harris Corner Detection for Eyes Detection in Facial Images

  • Navastara, Dini Adni;Koo, Kyung-Mo;Park, Hyun-Jun;Cha, Eui-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.373-376
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    • 2013
  • Nowadays, eyes detection is required and considered as the most important step in several applications, such as eye tracking, face identification and recognition, facial expression analysis and iris detection. This paper presents the eyes detection in facial images using Harris corner detection. Firstly, Haar-like features for face detection is used to detect a face region in an image. To separate the region of the eyes from a whole face region, the projection function is applied in this paper. At the last step, Harris corner detection is used to detect the eyes location. In experimental results, the eyes location on both grayscale and color facial images were detected accurately and effectively.

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Detection of Facial Features Using Color and Facial Geometry (색 정보와 기하학적 위치관계를 이용한 얼굴 특징점 검출)

  • 정상현;문인혁
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.57-60
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    • 2002
  • Facial features are often used for human computer interface(HCI). This paper proposes a method to detect facial features using color and facial geometry information. Face region is first extracted by using color information, and then the pupils are detected by applying a separability filter and facial geometry constraints. Mouth is also extracted from Cr(coded red) component. Experimental results shows that the proposed detection method is robust to a wide range of facial variation in position, scale, color and gaze.

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Detection of Facial Region and features from Color Images based on Skin Color and Deformable Model (스킨 컬러와 변형 모델에 기반한 컬러영상으로부터의 얼굴 및 얼굴 특성영역 추출)

  • 민경필;전준철;박구락
    • Journal of Internet Computing and Services
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    • v.3 no.6
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    • pp.13-24
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    • 2002
  • This paper presents an automatic approach to detect face and facial feature from face images based on the color information and deformable model. Skin color information has been widely used for face and facial feature diction since it is effective for object recognition and has less computational burden, In this paper, we propose how to compensates varying light condition and utilize the transformed YCbCr color model to detect candidates region of face and facial feature from color images, Moreover, the detected face facial feature areas are subsequently assigned to a initial condition of active contour model to extract optimal boundaries of face and facial feature by resolving initial boundary problem when the active contour is used, The experimental results show the efficiency of the proposed method, The face and facial feature information will be used for face recognition and facial feature descriptor.

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Effect of Acupuncture and High Frequency Therapy Applied to the Region Branching to the External Carotid Artery on Reduction of Facial Edema in Patients with Sequelae of Peripheral Facial Palsy: A Case Report (말초성 안면마비 후유증 환자에서 침 치료와 바깥목동맥으로의 분지 영역에 시행한 고주파 병행 치료의 안면부종 감소 효과: 증례보고)

  • An, Sunjoo;Choi, Seonghwan;Kang, Shinwoo;Park, Seohyun;Keum, Dongho
    • Journal of Korean Medicine Rehabilitation
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    • v.30 no.4
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    • pp.233-241
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    • 2020
  • This study was performed to evaluate the effect of high frequency therapy applied to the region branching to the external carotid artery for peripheral facial paralysis sequelae. A patient suffering with facial edema due to facial paralysis sequelae had been treated with acupuncture, high frequency therapy on the branch area to the external carotid artery for 7 weeks. The evaluation of clinical outcome was done by degree of swelling by measuring the distance of the face and skin temperature of face through digital infrared thermographic imaging. After treatment, the patient's degree of swelling and the temperature difference between the affected side and normal side was decreased. In addition, the temperature was changed in the entire facial area as well as the treatment point of high frequency therapy. This result shows that acupuncture combined with high frequency therapy at the region branching to the external carotid artery could be an effective way to improve facial blood flow, although further clinical studies will be needed.

Facial Region Tracking in YCbCr Color Coordinates (YCbCr 컬러 영상 변환을 통한 얼굴 영역 자동 검출)

  • Han, M.H.;Kim, K.S.;Yoon, T.H.;Shin, S.W.;Kim, I.Y.
    • Proceedings of the KIEE Conference
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    • 2005.05a
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    • pp.63-65
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    • 2005
  • In this study, the automatic face tracking algorithm is proposed by using the color and edge information of a color image. To reduce the effects of variations in the illumination conditions, an acquired CCD color image is first transformed into YCbCr color coordinates, and subsequently the morphological image processing operations, and the elliptical geometric measures are applied to extract the refined facial area.

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Local Feature Based Facial Expression Recognition Using Adaptive Decision Tree (적응형 결정 트리를 이용한 국소 특징 기반 표정 인식)

  • Oh, Jihun;Ban, Yuseok;Lee, Injae;Ahn, Chunghyun;Lee, Sangyoun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39A no.2
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    • pp.92-99
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    • 2014
  • This paper proposes the method of facial expression recognition based on decision tree structure. In the image of facial expression, ASM(Active Shape Model) and LBP(Local Binary Pattern) make the local features of a facial expressions extracted. The discriminant features gotten from local features make the two facial expressions of all combination classified. Through the sum of true related to classification, the combination of facial expression and local region are decided. The integration of branch classifications generates decision tree. The facial expression recognition based on decision tree shows better recognition performance than the method which doesn't use that.

3D Head Pose Estimation Using The Stereo Image (스테레오 영상을 이용한 3차원 포즈 추정)

  • 양욱일;송환종;이용욱;손광훈
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.1887-1890
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    • 2003
  • This paper presents a three-dimensional (3D) head pose estimation algorithm using the stereo image. Given a pair of stereo image, we automatically extract several important facial feature points using the disparity map, the gabor filter and the canny edge detector. To detect the facial feature region , we propose a region dividing method using the disparity map. On the indoor head & shoulder stereo image, a face region has a larger disparity than a background. So we separate a face region from a background by a divergence of disparity. To estimate 3D head pose, we propose a 2D-3D Error Compensated-SVD (EC-SVD) algorithm. We estimate the 3D coordinates of the facial features using the correspondence of a stereo image. We can estimate the head pose of an input image using Error Compensated-SVD (EC-SVD) method. Experimental results show that the proposed method is capable of estimating pose accurately.

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A study of face detection using color component (색상요소를 고려한 얼굴검출에 대한 연구)

  • 이정하;강진석;최연성;김장형
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.11a
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    • pp.240-243
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    • 2002
  • In this paper, we propose a face region detection based on skin-color distribution and facial feature extraction algorithm in color still images. To extract face region, we transform color using general skin-color distribution. Facial features are extracted by edge transformation. This detection process reduces calculation time by a scale-down scanning from segmented region. we can detect face region in various facial Expression, skin-color deference and tilted face images.

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