• Title/Summary/Keyword: 얼굴 텍스쳐 공간 모델링

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Face Illumination Normalization based on Illumination-Separated Face Identity Texture Subspace (조명영향 분리 얼굴 고유특성 텍스쳐 부분공간 기반 얼굴 이미지 조명 정규화)

  • Choi, Jong-Keun;Chung, Sun-Tae;Cho, Seong-Won
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.1
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    • pp.25-34
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    • 2010
  • Robust face recognition under various illumination environments is difficult to achieve. For robust face recognition with respect to illumination variations, illumination normalization of face images is usually applied as a preprocessing step. Most of previously proposed illumination normalization methods cannot handle cast shadows in face images effectively. In this paper, We propose a new face illumination normalization method based on the illumination-separated face identity texture subspace. Since the face identity texture subspace is constructed so as to be separated from the effects of illumination variations, the projection of face images into the subspace produces a good illumination-normalized face images. Through experiments, it is shown that the proposed face illumination normalization method can effectively eliminate cast shadows as well as attached shadows and achieves a good face illumination normalization.

3D Face Modeling based on 3D Morphable Shape Model (3D 변형가능 형상 모델 기반 3D 얼굴 모델링)

  • Jang, Yong-Suk;Kim, Boo-Gyoun;Cho, Seong-Won;Chung, Sun-Tae
    • The Journal of the Korea Contents Association
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    • v.8 no.1
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    • pp.212-227
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    • 2008
  • Since 3D face can be rotated freely in 3D space and illumination effects can be modeled properly, 3D face modeling Is more precise and realistic in face pose, illumination, and expression than 2D face modeling. Thus, 3D modeling is necessitated much in face recognition, game, avatar, and etc. In this paper, we propose a 3D face modeling method based on 3D morphable shape modeling. The proposed 3D modeling method first constructs a 3D morphable shape model out of 3D face scan data obtained using a 3D scanner Next, the proposed method extracts and matches feature points of the face from 2D image sequence containing a face to be modeled, and then estimates 3D vertex coordinates of the feature points using a factorization based SfM technique. Then, the proposed method obtains a 3D shape model of the face to be modeled by fitting the 3D vertices to the constructed 3D morphable shape model. Also, the proposed method makes a cylindrical texture map using 2D face image sequence. Finally, the proposed method builds a 3D face model by rendering the 3D face shape model with the cylindrical texture map. Through building processes of 3D face model by the proposed method, it is shown that the proposed method is relatively easy, fast and precise than the previous 3D face model methods.