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A Nonparametric Approach to Face Detection Using Ranklets

  • Fabrizio Smeraldi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2688)

Abstract

Ranklets are multiscale, orientation-selective, nonparametric rank features similar to Haar wavelets, suitable for characterising complex patterns. In this work, we employ a vector of ranklets to encode the appearance of an image frame representing a potential face candidate. Classification is based on density estimation by means of regularised histograms. Our procedure outperforms SNoW, linear and polynomial SVMs (based on independently published results) in face detection experiments over the 24’045 test images in the MIT-CBCL database.

Keywords

Face Detection Nonparametric Approach Haar Wavelet Univariate Density Equal Error 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 2003

Authors and Affiliations

  • Fabrizio Smeraldi
    • 1
  1. 1.Queen MaryUniversity of LondonLondonUK

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