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3-D face structure extraction and recognition from images using 3-D morphing and distance mapping.

Chongzhen Zhang1, Fernand S Cohen

  • 1Robotic Vision Systems, Inc., Hauppauge, NY 11788, USA. czzhang@cbis.ece.drexel.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 6, 2008
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Summary

This study introduces a new method to create 3-D face models from various images, enabling accurate pose estimation and identification using a novel distance map metric for robust face recognition.

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Area of Science:

  • Computer Vision
  • Biometrics
  • 3D Reconstruction

Background:

  • Accurate 3D face reconstruction from unconstrained images is challenging.
  • Pose estimation and identification require robust facial representations.

Purpose of the Study:

  • To develop a novel approach for 3D face structure creation from multiple, arbitrarily posed images.
  • To enable accurate pose estimation and face identification using the generated 3D face model.

Main Methods:

  • Morphing a generic 3D face model using cubic explicit polynomials.
  • Employing a distance map metric for 3D face and pose estimation.
  • Fusing geometric (distance map residual error) and intensity residual errors for identification.

Main Results:

  • Successful generation of 3D face structures from unknown poses.
  • Accurate pose estimation and virtual image synthesis.
  • Promising face identification results on simulated and real face images, even with noise.

Conclusions:

  • The proposed method effectively reconstructs 3D face structures and facilitates accurate pose estimation.
  • Fusion of geometric and intensity features enhances face identification robustness.
  • This approach offers a promising solution for unconstrained face recognition applications.