Heterogeneous Face Recognition from Local Structures of Normalized Appearance

  • Authors:
  • Shengcai Liao;Dong Yi;Zhen Lei;Rui Qin;Stan Z. Li

  • Affiliations:
  • Center for Biometrics and Security Research, Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190;Center for Biometrics and Security Research, Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190;Center for Biometrics and Security Research, Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190;Center for Biometrics and Security Research, Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190;Center for Biometrics and Security Research, Institute of Automation, Chinese Academy of Sciences, Beijing, China 100190

  • Venue:
  • ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
  • Year:
  • 2009

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Abstract

Heterogeneous face images come from different lighting conditions or different imaging devices, such as visible light (VIS) and near infrared (NIR) based. Because heterogeneous face images can have different skin spectra-optical properties, direct appearance based matching is no longer appropriate for solving the problem. Hence we need to find facial features common in heterogeneous images. For this, first we use Difference-of-Gaussian filtering to obtain a normalized appearance for all heterogeneous faces. We then apply MB-LBP, an extension of LBP operator, to encode the local image structures in the transformed domain, and further learn the most discriminant local features for recognition. Experiments show that the proposed method significantly outperforms existing ones in matching between VIS and NIR face images.