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Human ear recognition in 3D.

Hui Chen1, Bir Bhanu

  • 1University of California at Riverside, Riverside, CA 92521, USA. hchen@cris.ucr.edu

IEEE Transactions on Pattern Analysis and Machine Intelligence
|February 15, 2007
PubMed
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This study introduces a novel 3D ear biometrics system for human recognition. The system effectively detects, identifies, and verifies individuals using 3D ear shape and local surface patch representations.

Area of Science:

  • Biometrics
  • Computer Vision
  • Pattern Recognition

Background:

  • Human ear biometrics offer a stable and unique identification method.
  • Existing 3D ear recognition systems require further development in detection and feature representation.

Purpose of the Study:

  • To propose a complete 3D ear biometrics system for human recognition.
  • To introduce novel algorithms for 3D ear detection, identification, and verification.

Main Methods:

  • A novel 3D ear detection approach using a single reference model to locate helix and antihelix in 2D/3D images.
  • Two new representations for ear identification/verification: ear helix/antihelix and local surface patch (LSP).
  • Modified Iterative Closest Point (ICP) algorithm for refining rigid transformations between 3D ear models.

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Main Results:

  • The proposed system demonstrates effectiveness in 3D ear detection, identification, and verification.
  • Experimental results on UCR and University of Notre Dame datasets show robust performance under pose variations and time-lapse conditions.

Conclusions:

  • The developed 3D ear biometrics system provides a viable solution for human recognition.
  • The novel detection and representation methods enhance the accuracy and reliability of 3D ear-based identification and verification.