In this paper, we propose a face detection method by combining classifiers. We apply two classifiers using features extracted from complementary feature subspaces learned by principal component analysis (PCA). The two classifiers employ the same classification model named a polynomial neural network (PNN). The outputs of the two classifiers are fused to make the final decision. The effectiveness of the proposed method has been demonstrated in experimentals. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Huang, L. L., & Shimizu, A. (2006). Combining classifiers for robust face detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3972 LNCS, pp. 116–121). Springer Verlag. https://doi.org/10.1007/11760023_18
Mendeley helps you to discover research relevant for your work.