Abstract
In this paper, we present an ordinal feature based method for face recognition. Ordinal features are used to represent faces. Hamming distance of many local sub-windows is computed to evaluate differences of two ordinal faces. AdaBoost learning is finally applied to select most effective hamming distance based weak classifiers and build a powerful classifier. Experiments demonstrate good results for face recognition on the FERET database, and the power of learning ordinal features for face recognition.
This work was supported by Chinese National 863 Projects 2004AA1Z2290 & 2004AA119050.
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Liao, S., Lei, Z., Zhu, X., Sun, Z., Li, S.Z., Tan, T. (2005). Face Recognition Using Ordinal Features. In: Zhang, D., Jain, A.K. (eds) Advances in Biometrics. ICB 2006. Lecture Notes in Computer Science, vol 3832. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11608288_6
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DOI: https://doi.org/10.1007/11608288_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31111-9
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