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Extracting Scene-Dependent Discriminant Features for Enhancing Face Recognition under Severe Conditions

  • Rui Ishiyama
  • Nobuyuki Yasukawa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6469)

Abstract

This paper proposes a new method to compare similarities of candidate models that are fitted to different areas of a query image. This method extracts the discriminant features that are changed due to the varying pose/lighting condition of given query image, and the confidence of each model-fitting is evaluated based on how much of the discriminant features is captured in each foreground. The confidence is fused with the similarity to enhance the face-identification performance. In an experiment using 7,000 images of 200 subjects taken under largely varying pose and lighting conditions, our proposed method reduced the recognition errors by more than 25% compared to the conventional method.

Keywords

Reconstructed Image Face Recognition Similarity Score Query Image Appearance Model 
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 2011

Authors and Affiliations

  • Rui Ishiyama
    • 1
  • Nobuyuki Yasukawa
    • 1
  1. 1.Information and Media Processing Research LaboratoriesNEC CorporationKawasakiJapan

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