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. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Liao, S., Lei, Z., Zhu, X., Sun, Z., Li, S. Z., & Tan, T. (2006). Face recognition using ordinal features. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3832 LNCS, pp. 40–46). https://doi.org/10.1007/11608288_6
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