AFFINE-INVARIANT RECOGNITION OF FACE IMAGES USING GAT CORRELATION(International Workshop on Advanced Image Technology 2006)

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概要

• 論文の詳細を見る

• This paper addresses a challenging problem of performing normalization and recognition of face images at one time. The key idea is use of GAT (Global Affine Transformation) correlation for determining optimal 2D affine parameters that normalize a given image to yield the maximum correlation value with a target image. In our proposed method an input image is assigned to the enrolled face image associated with the largest GAT correlation value between the two images. By using 300 faces×8 images (4 frontal and 4 near-frontal images) extracted from the public HOIP face image database subject to no normalization we show that the proposed method achieves a very high recognition rate of 99.79% as compared to that of 98.46% obtained by the well-known eigenface method as applied only to manually normalized face images.

• 社団法人電子情報通信学会の論文
• 2006-01-03

著者

• Wakahara Toru

  Faculty Of Computer And Information Sciences Hosei University

• Makino Shinya

  Faculty Of Computer And Information Sciences Hosei University

関連論文

• AFFINE-INVARIANT RECOGNITION OF FACE IMAGES USING GAT CORRELATION(International Workshop on Advanced Image Technology 2006)
• Evaluation of GAT Correlation's Ability in Affine-Invariant Matching of Gray-Scale Face Images(Biometrics2)

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