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.
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© 2001 Springer-Verlag Berlin Heidelberg
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Ma, K., Tang, X. (2001). Translation-Invariant Face Feature Estimation Using Discrete Wavelet Transform. In: Tang, Y.Y., Yuen, P.C., Li, Ch., Wickerhauser, V. (eds) Wavelet Analysis and Its Applications. WAA 2001. Lecture Notes in Computer Science, vol 2251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45333-4_25
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DOI: https://doi.org/10.1007/3-540-45333-4_25
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Online ISBN: 978-3-540-45333-8
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