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Pose Invariant Face Recognition Under Arbitrary Illumination Based on 3D Face Reconstruction

  • Xiujuan Chai
  • Laiyun Qing
  • Shiguang Shan
  • Xilin Chen
  • Wen Gao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3546)

Abstract

Pose and illumination changes from picture to picture are two main barriers toward full automatic face recognition. In this paper, a novel method to handle both pose and lighting condition simultaneously is proposed, which calibrates the pose and lighting condition to a pre-set reference condition through an illumination invariant 3D face reconstruction. First, some located facial landmarks and a priori statistical deformable 3D model are used to recover an elaborate 3D shape. Based on the recovered 3D shape, the “texture image” calibrated to a standard illumination is generated by spherical harmonics ratio image and finally the illumination independent 3D face is reconstructed completely. The proposed method combines the strength of statistical deformable model to describe the shape information and the compact representations of the illumination in spherical frequency space, and handle both the pose and illumination variation simultaneously. This algorithm can be used to synthesize virtual views of a given face image and enhance the performance of face recognition. The experimental results on CMU PIE database show that this method can significantly improve the accuracy of the existed face recognition method when pose and illumination are inconsistent between gallery and probe sets.

Keywords

Face Recognition Face Image Texture Image Face Recognition System Gallery Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Xiujuan Chai
    • 1
  • Laiyun Qing
    • 2
  • Shiguang Shan
    • 2
  • Xilin Chen
    • 1
    • 2
  • Wen Gao
    • 1
    • 2
  1. 1.School of Computer Science and TechnologyHarbin Institute of TechnologyHarbinChina
  2. 2.ICT-ISVISION Joint R&D Lab for Face RecognitionICT, CASBeijingChina

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