The 3DID face alignment system for verifying identity

  • Authors:
  • Dirk Colbry;George Stockman

  • Affiliations:
  • Center for Cognitive Ubiquitous Computing, School of Computing and Informatics, Arizona State University, Tempe, AZ 85287-8807, USA;Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824-1226, USA

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2009

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Abstract

The 3DID system verifies the identity of a cooperative person by matching a sensed 3D surface of the face to a face model stored during a prior enrollment. First, anchor point detection is performed based on a shape index; then, a rigid alignment is determined between the observed and model face anchor points. A best alignment is determined using an improved Iterative Closest Point (ICP) algorithm that aligns the surfaces allowing for trimming of 10% noise points. Trimmed Root Mean Squared (RMS) error for the same person is almost always smaller than 1.3mm; whereas for different persons, it is almost always larger than this threshold. Performance analysis shows that the 3DID system is fast enough (