In this paper, we propose a new method of extracting the discriminative features for classification from a given training dataset. The proposed method combines the advantages of both the null space method and the maximum margin criterion (MMC) method, whilst overcomes their drawbacks. The better performance of the proposed method is confirmed by face recognition experiments. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Zheng, W., Zou, C., & Zhao, L. (2005). Discriminative features extraction in minor component subspace. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3784 LNCS, pp. 218–223). https://doi.org/10.1007/11573548_28
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