3D Face Recognition Using Parallel Pyramid Neural Networks

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In this paper, we propose a method of 3D face recognition using parallel pyramid neural networks (NNs). We first compensate for the poses of 3D original facial images using feature points and geometrical measurement. Then, the shape and texture images are extracted from compensated 3D images, respectively. The dimensionalities of the shape and texture images are reduced using PCA, processed by LDA for enhanced generalization. The corresponding reduced shape and texture features are combined to form the integrated features for face recognition. In the second step, a method is proposed for face recognition based on parallel pyramid NNs. Compared with conventional NN, the performance of the proposed parallel pyramid NNs is improved by utilizing lower layer effectively. Experimental results for 60 persons with different poses, facial expression and illumination conditions demonstrate the efficiency of our algorithm. In particular, the proposed method achieves 99.17% recognition accuracy using only 120 features.

収録刊行物

  • 電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society  

    電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society 126(8), 963-971, 2006-08-01 

    The Institute of Electrical Engineers of Japan

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各種コード

  • NII論文ID(NAID)
    10018181849
  • NII書誌ID(NCID)
    AN10065950
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    03854221
  • NDL 記事登録ID
    8054371
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-795
  • データ提供元
    CJP書誌  NDL  J-STAGE 
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