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      • Computing and Mathematical Sciences
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      A hierarchical face recognition algorithm

      Bouckaert, Remco R.
      DOI
       10.1007/978-3-642-05224-8_5
      Link
       link.springer.com
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      Citation
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      Bouckaert, 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.
      Permanent Research Commons link: https://hdl.handle.net/10289/8015
      Abstract
      In 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.
      Date
      2009
      Type
      Conference Contribution
      Publisher
      Springer
      Collections
      • Computing and Mathematical Sciences Papers [1454]
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