• Title/Summary/Keyword: 3차원 얼굴

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A Study on 3D Face Modelling based on Dynamic Muscle Model for Face Animation (얼굴 애니메이션을 위한 동적인 근육모델에 기반한 3차원 얼굴 모델링에 관한 연구)

  • 김형균;오무송
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.2
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    • pp.322-327
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    • 2003
  • Based on dynamic muscle model to construct efficient face animation in this paper 30 face modelling techniques propose. Composed face muscle by faceline that connect 256 point and this point based on dynamic muscle model, and constructed wireframe because using this. After compose standard model who use wireframe, because using front side and side 2D picture, enforce texture mapping and created 3D individual face model. Used front side of characteristic points and side part for correct mapping, after make face that have texture coordinates using 2D coordinate of front side image and front side characteristic points, constructed face that have texture coordinates using 2D coordinate of side image and side characteristic points.

Design of Three-dimensional Face Recognition System Using Optimized PRBFNNs and PCA : Comparative Analysis of Evolutionary Algorithms (최적화된 PRBFNNs 패턴분류기와 PCA알고리즘을 이용한 3차원 얼굴인식 알고리즘 설계 : 진화 알고리즘의 비교 해석)

  • Oh, Sung-Kwun;Oh, Seung-Hun;Kim, Hyun-Ki
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.6
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    • pp.539-544
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    • 2013
  • In this paper, we was designed three-dimensional face recognition algorithm using polynomial based RBFNNs and proposed method to calculate the recognition performance. In case of two-dimensional face recognition, the recognition performance is reduced by the external environment like facial pose and lighting. In order to compensate for these shortcomings, we perform face recognition by obtaining three-dimensional images. obtain face image using three-dimension scanner before the face recognition and obtain the front facial form using pose-compensation. And the depth value of the face is extracting using Point Signature method. The extracted data as high-dimensional data may cause problems in accompany the training and recognition. so use dimension reduction data using PCA algorithm. accompany parameter optimization using optimization algorithm for effective training. Each recognition performance confirm using PSO, DE, GA algorithm.

Face Muscle Modeling and Application Method using Bitmap Form (비트맵 형식을 이용한 얼굴 근육 모델링 및 적용방법)

  • Lee, Dong-Gyo;Jeong, Mun-Yeol;Baek, Du-Won
    • Journal of the Korea Computer Graphics Society
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    • v.8 no.4
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    • pp.17-25
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    • 2002
  • In this paper we propose a new efficient muscle modeling for creating 3d facial models. It improves the existing muscle-based facial modeling method. We present the facial muscle action prediction map as a new method of muscle modeling. We also suggest a new face deformation method that improves the existing method which controls each muscle's condition separately.

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3D Face Image Watermarking using Wavelet Transform (웨이브렛 변환을 이용한 3차원 얼굴영상 워터마킹)

  • 이정환;박세훈;이시웅
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.691-694
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    • 2003
  • This paper proposes an 3D face image watermarking method based on discrete wavelet transform(DWT). First, 3D face image are transformed by DWT and inserted gaussian watermark into frequency domain. To increase the robustness and perceptual invisibility of watermark, the proposed algorithm is combined with the characteristics of 3D face image and human visual system. The proposed method is invisible and blind watermarking which the original image is not required. Simulation results show that the proposed method is robust to the general attack such as JPEG compression, enhancement, noise, cropping, and filtering etc.

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A 3D Face Modeling Method Using Region Segmentation and Multiple light beams (지역 분할과 다중 라이트 빔을 이용한 3차원 얼굴 형상 모델링 기법)

  • Lee, Yo-Han;Cho, Joo-Hyun;Song, Tai-Kyong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.38 no.6
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    • pp.70-81
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    • 2001
  • This paper presents a 3D face modeling method using a CCD camera and a projector (LCD projector or Slide projector). The camera faces the human face and the projector casts white stripe patterns on the human face. The 3D shape of the face is extracted from spatial and temporal locations of the white stripe patterns on a series of image frames. The proposed method employs region segmentation and multi-beam techniques for efficient 3D modeling of hair region and faster 3D scanning respectively. In the proposed method, each image is segmented into face, hair, and shadow regions, which are independently processed to obtain the optimum results for each region. The multi-beam method, which uses a number of equally spaced stripe patterns, reduces the total number of image frames and consequently the overall data acquisition time. Light beam calibration is adopted for efficient light plane measurement, which is not influenced by the direction (vertical or horizontal) of the stripe patterns. Experimental results show that the proposed method provides a favorable 3D face modeling results, including the hair region.

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Face Recognition Based on Weighted Hausdorff Distance for Profile Image (가중치 하우스도르프 거리를 이용한 프로파일 얼굴인식)

  • 이영학
    • Journal of Korea Multimedia Society
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    • v.7 no.4
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    • pp.474-483
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    • 2004
  • In this paper, we present a new Practical implementation of a person verification system using the profile of 3-dimensional(3D) face images based on weighted Hausdorff distance(WHD) used depth information. The approach works on finding the nose tip have protrusion shape on the face using iterative selection method to use a fiducial feint and extract the profile image from vertical 3D data for the nose tip. Hausdorff distance(HD) is one of usually used measures for object matching. This works analyze the conventional HD and WHD, which the weighted factor is depth information. The Ll measure for comparing two feature vectors were used, because it is simple and robust. In the experimental results, the WHD method achieves recognition rate of 94.3% when the ranked threshold is 5.

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Realistic Skin Rendering for 3D Facial Makeup (3차원 얼굴 메이크업을 위한 사실적인 피부 렌더링)

  • Lee, Sang-Hoon;Kim, Hyeon-Joong;Choi, Soo-Mi
    • Journal of Korea Multimedia Society
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    • v.16 no.4
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    • pp.520-528
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    • 2013
  • Makeup simulation is a tool that tests various makeup methods on a virtual digital face using input and display devices. Although several simulation systems supporting various makeup styles have been recently developed, most systems have many limitations on realistic skin representations because they use 2D facial images. We develope a realistic makeup simulation method which can control skin reflectance and roughness parameters. The method allows a user to simulate makeup applications while changing skin parameters using high-resolution facial data acquired by 3D scanners. Besides we use a point-based shape representation which enables simple and flexible 3D rendering, and provide a more realistic makeup simulation by applying different skin parameters on each part of the face.

Automatic Generation of the Personal 3D Face Model (3차원 개인 얼굴 모델 자동 생성)

  • Ham, Sang-Jin;Kim, Hyoung-Gon
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.1
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    • pp.104-114
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    • 1999
  • This paper proposes an efficient method for the automatic generation of personalized 3D face model from color image sequence. To detect a robust facial region in a complex background, moving color detection technique based on he facial color distribution has been suggested. Color distribution and edge position information in the detected face region are used to extract the exact 31 facial feature points of the facial description parameter(FDP) proposed by MPEG-4 SNHC(Synthetic-Natural Hybrid Coding) adhoc group. Extracted feature points are then applied to the corresponding vertex points of the 3D generic face model composed of 1038 triangular mesh points. The personalized 3D face model can be generated automatically in less then 2 seconds on Pentium PC.

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Automatic Mask Generation for 3D Makeup Simulation (3차원 메이크업 시뮬레이션을 위한 자동화된 마스크 생성)

  • Kim, Hyeon-Joong;Kim, Jeong-Sik;Choi, Soo-Mi
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.397-402
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    • 2008
  • 본 논문에서는 햅틱 인터랙션 기반의 3차원 가상 얼굴 메이크업 시뮬레이션에서 메이크업 대상에 대한 정교한 페인팅을 적용하기 위한 자동화된 마스크 생성 방법을 개발한다. 본 연구에서는 메이크업 시뮬레이션 이전의 전처리 과정에서 마스크를 생성한다. 우선, 3차원 스캐너 장치로부터 사용자의 얼굴 텍스쳐 이미지와 3차원 기하 표면 모델을 획득한다. 획득된 얼굴 텍스쳐 이미지로부터 AdaBoost 알고리즘, Canny 경계선 검출 방법과 색 모델 변환 방법 등의 영상처리 알고리즘들을 적용하여 마스크 대상이 되는 주요 특정 영역(눈, 입술)들을 결정하고 얼굴 이미지로부터 2차원 마스크 영역을 결정한다. 이렇게 생성된 마스크 영역 이미지는 3차원 표면 기하 모델에 투영되어 최종적인 3차원 특징 영역의 마스크를 레이블링하는데 사용된다. 이러한 전처리 과정을 통하여 결정된 마스크는 햅틱 장치와 스테레오 디스플레이기반의 가상 인터페이스를 통해서 자연스러운 메이크업 시뮬레이션을 수행하는데 사용된다. 본 연구에서 개발한 방법은 사용자에게 전처리 과정에서의 어떠한 개입 없이 자동적으로 메이크업 대상이 되는 마스크 영역을 결정하여 정교하고 손쉬운 메이크업 페인팅 인터페이스를 제공한다.

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3D Facial Expression Creation System Based on Muscle Model (근육모델 기반의 3차원 얼굴표정 생성시스템)

  • 이현철;윤재홍;허기택
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.05c
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    • pp.465-468
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    • 2002
  • 최근 컴퓨터를 이용한 시각 분야가 발전하면서 인간과 관계된 연구가 중요시 되어, 사람과 컴퓨터의 인터페이스에 대한 새로운 시도들이 다양하게 이루어지고 있다. 특히 얼굴 형상 모델링과 얼굴 표정변화를 애니메이션 화하는 방법에 대한 연구가 활발히 수행되고 있으며, 그 용도가 매우 다양하고, 적용 범위도 증가하고 있다. 본 논문에서는 한국인의 얼굴특성에 맞는 표준적인 일반모델을 생성하고, 실제 사진과 같이 개개인의 특성에 따라 정확한 형상을 유지할 수 있는 3차원 형상 모델을 제작한다. 그리고 자연스러운 얼굴 표정 생성을 위하여, 근육모델 기반의 얼굴표정 생성 시스템을 개발하여, 자연스럽고 실제감 있는 얼굴애니메이션이 이루어질 수 있도록 하였다.

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