Robust Face Detection Using the Hausdorff Distance

  • Oliver Jesorsky
  • Klaus J. Kirchberg
  • Robert W. Frischholz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2091)

Abstract

The localization of human faces in digital images is a fundamental step in the process of face recognition. This paper presents a shape comparison approach to achieve fast, accurate face detection that is robust to changes in illumination and background. The proposed method is edge-based and works on grayscale still images. The Hausdorff distance is used as a similarity measure between a general face model and possible instances of the object within the image. The paper describes an efficient implementation, making this approach suitable for real-time applications. A two-step process that allows both coarse detection and exact localization of faces is presented. Experiments were performed on a large test set base and rated with a new validation measurement.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Oliver Jesorsky
    • 1
  • Klaus J. Kirchberg
    • 1
  • Robert W. Frischholz
    • 1
  1. 1.BioID AGBerlinGermany

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