• Title/Summary/Keyword: Face Shape Estimation

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3D Human Face Segmentation using Curvature Estimation (Curvature Estimation을 이용한 3차원 사람얼굴 세그멘테이션)

  • Seongdong Kim;Seonga Chin;Moonwon Choo
    • Journal of Korea Multimedia Society
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    • v.6 no.6
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    • pp.985-990
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    • 2003
  • This paper presents the representation and its shape analysis of face by features based on surface curvature estimation and proposed rotation vector of the human face. Curvature-based surface features are well suited to use for experimenting the 3D human face segmentation. Human surfaces are exactly extracted and computed with parameters and rotated by using active surface mesh model. The estimated features were tested and segmented by reconstructing surfaces from the face surface and analytically computing Gaussian (K) and mean (H) curvatures without threshold.

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Facial Feature Extraction with Its Applications

  • Lee, Minkyu;Lee, Sangyoun
    • Journal of International Society for Simulation Surgery
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    • v.2 no.1
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    • pp.7-9
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    • 2015
  • Purpose In the many face-related application such as head pose estimation, 3D face modeling, facial appearance manipulation, the robust and fast facial feature extraction is necessary. We present the facial feature extraction method based on shape regression and feature selection for real-time facial feature extraction. Materials and Methods The facial features are initialized by statistical shape model and then the shape of facial features are deformed iteratively according to the texture pattern which is selected on the feature pool. Results We obtain fast and robust facial feature extraction result with error less than 4% and processing time less than 12 ms. The alignment error is measured by average of ratio of pixel difference to inter-ocular distance. Conclusion The accuracy and processing time of the method is enough to apply facial feature based application and can be used on the face beautification or 3D face modeling.

3D Face Modeling using Face Image

  • Kim, Sanghyuk;Ban, Yuseok;Park, Changhyun;Lee, Sangyoun
    • Journal of International Society for Simulation Surgery
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    • v.2 no.1
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    • pp.10-12
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    • 2015
  • Purpose It has been stated that patient satisfaction is the crucial factor for determining success in plastic surgery. The convergence of medical science and computer vision has made easier to satisfy patients who wants to have plastic surgery. In this paper, we try to apply 3D face modeling in plastic surgical area. Materials and Methods The author introduces a method for accurate 3D face modeling techniques using a statistical model-based 3D face modeling approach in a mirror system. Results We could successfully obtain highly accurate 3D face shape results. Conclusion The method suggested could be used for acquiring 3D face models from 2D face image and the result obtained from this could be effectively used for plastic surgical areas.

Face Transform with Age-progressing based on Vector Representation (벡터표현 기반의 연령변화에 따른 얼굴 변환)

  • Lee, Hyun-jik;Kim, Yoon-Ho
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.3 no.3
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    • pp.39-44
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    • 2010
  • In this paper, we addressed a face transform scheme with age-progressing based on vector representation. Proposed approach utilized a vector modeling as well as morphing so as to improve not only a reliability but also a consistency. For the more, some elements of texture change owing to the face shape are defined and some parameters with respect to the internal and external environments are also considered. To testify the proposed approach, estimation of similarity is performed with qualitative manner by using experimental output, and finally resulted in satisfactory for face shape transformation aged from sixty to fourteen.

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Detection of Face and Facial Features in Complex Background from Color Images (복잡한 배경의 칼라영상에서 Face and Facial Features 검출)

  • 김영구;노진우;고한석
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.69-72
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    • 2002
  • Human face detection has many applications such as face recognition, face or facial feature tracking, pose estimation, and expression recognition. We present a new method for automatically segmentation and face detection in color images. Skin color alone is usually not sufficient to detect face, so we combine the color segmentation and shape analysis. The algorithm consists of two stages. First, skin color regions are segmented based on the chrominance component of the input image. Then regions with elliptical shape are selected as face hypotheses. They are certificated to searching for the facial features in their interior, Experimental results demonstrate successful detection over a wide variety of facial variations in scale, rotation, pose, lighting conditions.

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A 3D Face Reconstruction and Tracking Method using the Estimated Depth Information (얼굴 깊이 추정을 이용한 3차원 얼굴 생성 및 추적 방법)

  • Ju, Myung-Ho;Kang, Hang-Bong
    • The KIPS Transactions:PartB
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    • v.18B no.1
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    • pp.21-28
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    • 2011
  • A 3D face shape derived from 2D images may be useful in many applications, such as face recognition, face synthesis and human computer interaction. To do this, we develop a fast 3D Active Appearance Model (3D-AAM) method using depth estimation. The training images include specific 3D face poses which are extremely different from one another. The landmark's depth information of landmarks is estimated from the training image sequence by using the approximated Jacobian matrix. It is added at the test phase to deal with the 3D pose variations of the input face. Our experimental results show that the proposed method can efficiently fit the face shape, including the variations of facial expressions and 3D pose variations, better than the typical AAM, and can estimate accurate 3D face shape from images.

Active Shape Model with Directional Profile (방향성 프로파일을 적용한 능동형태 모델)

  • Kim, Jeong Yeop
    • Journal of Korea Multimedia Society
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    • v.20 no.11
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    • pp.1720-1728
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    • 2017
  • Active shape model is widely used in the field of image processing especially on arbitrary meaningful shape extraction from single gray level image. Cootes et. al. showed efficient detection of variable shape from image by using covariance and mean shape from learning. There are two stages of learning and testing. Hahn applied enhanced shape alignment method rather than using Cootes's rotation and scale scheme. Hahn did not modified the profile itself. In this paper, the method using directional one dimensional profile is proposed to enhance Cootes's one dimensional profile and the shape alignment algorithm of Hahn is combined. The performance of the proposed method was superior to Cootes's and Hahn's. Average landmark estimation error for each image was 27.72 pixels and 39.46 for Cootes's and 33.73 for Hahn's each.

Robust Real-time Tracking of Facial Features with Application to Emotion Recognition (안정적인 실시간 얼굴 특징점 추적과 감정인식 응용)

  • Ahn, Byungtae;Kim, Eung-Hee;Sohn, Jin-Hun;Kweon, In So
    • The Journal of Korea Robotics Society
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    • v.8 no.4
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    • pp.266-272
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    • 2013
  • Facial feature extraction and tracking are essential steps in human-robot-interaction (HRI) field such as face recognition, gaze estimation, and emotion recognition. Active shape model (ASM) is one of the successful generative models that extract the facial features. However, applying only ASM is not adequate for modeling a face in actual applications, because positions of facial features are unstably extracted due to limitation of the number of iterations in the ASM fitting algorithm. The unaccurate positions of facial features decrease the performance of the emotion recognition. In this paper, we propose real-time facial feature extraction and tracking framework using ASM and LK optical flow for emotion recognition. LK optical flow is desirable to estimate time-varying geometric parameters in sequential face images. In addition, we introduce a straightforward method to avoid tracking failure caused by partial occlusions that can be a serious problem for tracking based algorithm. Emotion recognition experiments with k-NN and SVM classifier shows over 95% classification accuracy for three emotions: "joy", "anger", and "disgust".

The Recoginition of Pattern of Shape and Composing the Graph Topology of Sketch Drawing Element for the Automation of Earthwork Quantity Calculation (토공수량계산 자동화를 위한 스케치 도면 요소의 그래프 위상 자동 구성 및 형태 패턴 인식에 대한 연구)

  • Kang, Tae-Wook;Kim, Bong-Seok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.2D
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    • pp.171-179
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    • 2010
  • The purpose of the present study is to suggest composing the graph topology of sketch drawing element and the recognition of the shape pattern for the earthwork quantity calculation. The algorithm which can extract the topology element such as vertex, edge, face and establish the relation between each topology was developed. The model which can define earthwork graph and recognize the shape pattern of earthwork was presented. As a result of the study, the shape pattern of earthwork that can't be calculated by existing earthwork calculation program could be recognized as expanding this model. The earthwork shape recognition automation using the graph topology model can be applied to the automation for the earthwork quantity estimation.

Estimation of wind pressure coefficients on multi-building configurations using data-driven approach

  • Konka, Shruti;Govindray, Shanbhag Rahul;Rajasekharan, Sabareesh Geetha;Rao, Paturu Neelakanteswara
    • Wind and Structures
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    • v.32 no.2
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    • pp.127-142
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    • 2021
  • Wind load acting on a standalone structure is different from that acting on a similar structure which is surrounded by other structures in close proximity. The presence of other structures in the surrounding can change the wind flow regime around the principal structure and thus causing variation in wind loads compared to a standalone case. This variation on wind loads termed as interference effect depends on several factors like terrain category, geometry of the structure, orientation, wind incident angle, interfering distances etc., In the present study, a three building configuration is considered and the mean pressure coefficients on each face of principle building are determined in presence of two interfering buildings. Generally, wind loads on interfering buildings are determined from wind tunnel experiments. Computational fluid dynamic studies are being increasingly used to determine the wind loads recently. Whereas, wind tunnel tests are very expensive, the CFD simulation requires high computational cost and time. In this scenario, Artificial Neural Network (ANN) technique and Support Vector Regression (SVR) can be explored as alternative tools to study wind loads on structures. The present study uses these data-driven approaches to predict mean pressure coefficients on each face of principle building. Three typical arrangements of three building configuration viz. L shape, V shape and mirror of L shape arrangement are considered with varying interfering distances and wind incidence angles. Mean pressure coefficients (Cp mean) are predicted for 45 degrees wind incidence angle through ANN and SVR. Further, the critical faces of principal building, critical interfering distances and building arrangement which are more prone to wind loads are identified through this study. Among three types of building arrangements considered, a maximum of 3.9 times reduction in Cp mean values are noticed under Case B (V shape) building arrangement with 2.5B interfering distance. Effect of interfering distance and building arrangement on suction pressure on building faces has also been studied. Accordingly, Case C (mirror of L shape) building arrangement at a wind angle of 45º shows less suction pressure. Through this study, it was also observed that the increase of interfering distance may increase the suction pressure for all the cases of building configurations considered.