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

Theoharis Theoharis, Georgios Passalis, George Toderici, Ioannis A. Kakadiaris

Research output: Contribution to journalArticlepeer-review

61 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)796-804
Number of pages9
JournalPattern Recognition
Volume41
Issue number3
DOIs
StatePublished - Mar 2008

Keywords

  • Deformable models
  • Ear recognition
  • Face recognition
  • Geometry images
  • Multimodal biometrics
  • Wavelets

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Unified 3D face and ear recognition using wavelets on geometry images'. Together they form a unique fingerprint.

Cite this