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3D Face Recognition Founded on the Structural Diversity of Human Faces

Shalini Gupta, J. K. Aggarwal, Mia K. Markey, Alan C. Bovik
CVPR 2007
doi:10.1109/CVPR.2007.383053 /cvpr/2007/gupta2007cvpr-d/

Abstract

We present a systematic procedure for selecting facial fiducial points associated with diverse structural characteristics of a human face. We identify such characteristics from the existing literature on anthropometric facial proportions. We also present three dimensional (3D) face recognition algorithms, which employ Euclidean/geodesic distances between these anthropometric fiducial points as features along with linear discriminant analysis classifiers. Furthermore, we show that in our algorithms, when anthropometric distances are replaced by distances between arbitrary regularly spaced facial points, their performances decrease substantially. This demonstrates that incorporating domain specific knowledge about the structural diversity of human faces significantly improves the performance of 3D human face recognition algorithms.

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Cite

Text

Gupta et al. "3D Face Recognition Founded on the Structural Diversity of Human Faces." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007. doi:10.1109/CVPR.2007.383053

Markdown

[Gupta et al. "3D Face Recognition Founded on the Structural Diversity of Human Faces." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2007.](https://mlanthology.org/cvpr/2007/gupta2007cvpr-d/) doi:10.1109/CVPR.2007.383053

BibTeX

@inproceedings{gupta2007cvpr-d,
  title     = {{3D Face Recognition Founded on the Structural Diversity of Human Faces}},
  author    = {Gupta, Shalini and Aggarwal, J. K. and Markey, Mia K. and Bovik, Alan C.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2007},
  doi       = {10.1109/CVPR.2007.383053},
  url       = {https://mlanthology.org/cvpr/2007/gupta2007cvpr-d/}
}