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Learning to recognize faces from examples

  • Shimon Edelman
  • Daniel Reisfeld
  • Yechezkel Yeshurun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)

Abstract

We describe an implemented system that learns to recognize human faces under varying pose and illumination conditions. The system relies on symmetry operations to detect the eyes and the mouth in a face image, uses the locations of these features to normalize the appearance of the face, performs simple but effective dimensionality reduction by a convolution with a set of Gaussian receptive fields, and subjects the vector of activities of the receptive fields to a Radial Basis Function interpolating classifier. The performance of the system compares favorably with the state of the art in machine recognition of faces.

Keywords

Face Recognition Receptive Field Object Recognition Face Image False Alarm Rate 
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 1992

Authors and Affiliations

  • Shimon Edelman
    • 1
  • Daniel Reisfeld
    • 2
  • Yechezkel Yeshurun
    • 2
  1. 1.Dept. of Applied Mathematics and Computer ScienceThe Weizmann Institute of ScienceRehovotIsrael
  2. 2.Dept. of Computer ScienceTel Aviv UniversityTel AvivIsrael

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