Translation-Invariant Face Feature Estimation Using Discrete Wavelet Transform

  • Authors:

  • Kun Ma;Xiaoou Tang

  • Affiliations:

  • -;-

  • Venue:
  • WAA '01 Proceedings of the Second International Conference on Wavelet Analysis and Its Applications
  • Year:
  • 2001

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Abstract

In this paper, we conduct a series of experiments to demonstrate the translation invariant property of a set of discrete wavelet features in a face graph. Using local-area power spectrum estimation based on discrete wavelet transform, we compute a feature vector that possesses both an efficient space-frequency structure and the translation invariant property.