ML Anthology

Performance of Geometrix ActiveIDTM 3D Face Recognition Engine on the FRGC Data

Thomas Maurer, David Guigonis, Igor Maslov, Bastien Pesenti, Alexei Tsaregorodtsev, David West, Gérard G. Medioni
CVPR 2005 pp. 154
doi:10.1109/CVPR.2005.581 /cvpr/2005/maurer2005cvpr-performance/

Abstract

We present and analyze the performance of the Geometrix ActiveIDTM Biometric Identity System on the FRGC data from Experiment 3, consisting of 4007 3D faces. The performance is presented and analyzed for different facial expression categories. We first present the Geometrix FaceVision 3D face recognition technology, then describe how shape and texture are fused. The effect of fusion on error rates is discussed, and the remaining errors are analyzed. We conclude with lessons learned, general findings, and what we expect in the near future.

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Cite

Text

Maurer et al. "Performance of Geometrix ActiveIDTM 3D Face Recognition Engine on the FRGC Data." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005. doi:10.1109/CVPR.2005.581

Markdown

[Maurer et al. "Performance of Geometrix ActiveIDTM 3D Face Recognition Engine on the FRGC Data." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005.](https://mlanthology.org/cvpr/2005/maurer2005cvpr-performance/) doi:10.1109/CVPR.2005.581

BibTeX

@inproceedings{maurer2005cvpr-performance,
  title     = {{Performance of Geometrix ActiveIDTM 3D Face Recognition Engine on the FRGC Data}},
  author    = {Maurer, Thomas and Guigonis, David and Maslov, Igor and Pesenti, Bastien and Tsaregorodtsev, Alexei and West, David and Medioni, Gérard G.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2005},
  pages     = {154},
  doi       = {10.1109/CVPR.2005.581},
  url       = {https://mlanthology.org/cvpr/2005/maurer2005cvpr-performance/}
}