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Rank-Based Decision Fusion for 3D Shape-Based Face Recognition

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Abstract

In 3D face recognition systems, 3D facial shape information plays an important role. Various shape representations have been proposed in the literature. The most popular techniques are based onpoint clouds,surface normals,facial profiles, and statistical analysis ofdepth images. The contribution of the presented work can be divided into two parts: In the first part, we have developed face classifiers which use these popular techniques. A comprehensive comparison of these representation methods are given using 3D RMA dataset. Experimental results show that thelinear discriminant analysis-based representation of depth images andpoint cloud representation perform best. In the second part of the paper, two different multiple-classifier architectures are developed to fuse individual shape-based face recognizers in parallel and hierarchical fashions at the decision level. It is shown that a significant performance improvement is possible when using rank-based decision fusion in ensemble methods.

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Author information

Authors and Affiliations

  1. Computer Engineering Department, Boğaziçi University, Turkey

    Berk Gökberk, Albert Ali Salah & Lale Akarun

Authors
  1. Berk Gökberk

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  2. Albert Ali Salah

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  3. Lale Akarun

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Editor information

Editors and Affiliations

  1. The Robotics Institute, Carnegie Mellon University., Pittsburgh, 15213-3890, Pennsylvania, USA

    Takeo Kanade

  2. Withington Hospital, Nightingale Centre, Manchester, UK

    Anil Jain

  3. IBM Thomas J. Watson Research Center, 19 Skyline Drive, NY 10598, Hawthorne, USA

    Nalini K. Ratha

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© 2005 Springer-Verlag Berlin Heidelberg

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Gökberk, B., Salah, A.A., Akarun, L. (2005). Rank-Based Decision Fusion for 3D Shape-Based Face Recognition. In: Kanade, T., Jain, A., Ratha, N.K. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2005. Lecture Notes in Computer Science, vol 3546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527923_106

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