Unified 3D face and ear recognition using wavelets on geometry images

  • Authors:

  • Theoharis Theoharis;Georgios Passalis;George Toderici;Ioannis A. Kakadiaris

  • Affiliations:

  • Computer Graphics Group, Department of Informatics and Telecommunications, University of Athens, Ilisia 15784, Greece and Computational Biomedicine Lab, Department of Computer Science, University ...;Computer Graphics Group, Department of Informatics and Telecommunications, University of Athens, Ilisia 15784, Greece and Computational Biomedicine Lab, Department of Computer Science, University ...;Computational Biomedicine Lab, Department of Computer Science, University of Houston, Texas 77204, USA;Computational Biomedicine Lab, Department of Computer Science, University of Houston, Texas 77204, USA

  • Venue:
  • Pattern Recognition
  • Year:
  • 2008

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Abstract

As the accuracy of biometrics improves, it is getting increasingly hard to push the limits using a single modality. In this paper, a unified approach that fuses three-dimensional facial and ear data is presented. An annotated deformable model is fitted to the data and a geometry image is extracted. Wavelet coefficients are computed from the geometry image and used as a biometric signature. The method is evaluated using the largest publicly available database and achieves 99.7% rank-one recognition rate. The state-of-the-art accuracy of the multimodal fusion is attributed to the low correlation between the individual differentiability of the two modalities.