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dc.contributor.authorBouckaert, Remco R.
dc.coverage.spatialConference held at Nanjing, Chinaen_NZ
dc.identifier.citationBouckaert, R. R. (2009). A hierarchical face recognition algorithm. In Z.-H. Zhou and T. Washio (Eds.), Proceedings of the First Asian Conference on Machine Learning, ACML 2009, Nanjing, China, November 2-4, 2009 (pp. 38-50). Berlin, Germany: Springer.en_NZ
dc.description.abstractIn this paper, we propose a hierarchical method for face recognition where base classifiers are defined to make predictions based on various different principles and classifications are combined into a single prediction. Some features are more relevant to particular face recognition tasks than others. The hierarchical algorithm is flexible in selecting features relevant for the face recognition task at hand. In this paper, we explore various features based on outline recognition, PCA classifiers applied to part of the face and exploitation of symmetry in faces. By combining the predictions of these features we obtain superior performance on benchmark datasets (99.25% accuracy on the ATT dataset) at reduced computation cost compared to full PCA.en_NZ
dc.subjectcomputer scienceen_NZ
dc.subjectartificial intelligenceen_NZ
dc.subjectdata miningen_NZ
dc.subjectcomputer imagingen_NZ
dc.subjectpattern recognitionen_NZ
dc.titleA hierarchical face recognition algorithmen_NZ
dc.typeConference Contributionen_NZ
dc.relation.isPartOfProc 1st Asian Conference on Machine Learning: Advances in Machine Learningen_NZ
pubs.volumeLNAI 5828en_NZ

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