Textural Hausdorff Distance for Wider-Range Tolerance to Pose Variation and Misalignment in 2D Face Recognition

CVPR 2009 pp. 1629-1634

doi:10.1109/CVPR.2009.5206798 /cvpr/2009/zhao2009cvpr-textural/

Abstract

This paper addresses two critical but rarely concerned issues in 2D face recognition: wider-range tolerance to pose variation and misalignment. We propose a new Textural Hausdorff Distance (THD), which is a compound measurement integrating both spatial and textural features. The THD is applied to a Significant Jet Point (SJP) representation of face images, where a varied number of shape-driven SJPs are detected automatically from low-level edge map with rich information content. The comparative experiments conducted on publicly available FERET and AR face databases demonstrated that the proposed approach has a considerably wider range of tolerance against both in-depth head rotation and face misalignment.

PDF CVPR Semantic Scholar

Cite

Text

Zhao and Gao. "Textural Hausdorff Distance for Wider-Range Tolerance to Pose Variation and Misalignment in 2D Face Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009. doi:10.1109/CVPR.2009.5206798

Markdown

[Zhao and Gao. "Textural Hausdorff Distance for Wider-Range Tolerance to Pose Variation and Misalignment in 2D Face Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009.](https://mlanthology.org/cvpr/2009/zhao2009cvpr-textural/) doi:10.1109/CVPR.2009.5206798

BibTeX

@inproceedings{zhao2009cvpr-textural,
  title     = {{Textural Hausdorff Distance for Wider-Range Tolerance to Pose Variation and Misalignment in 2D Face Recognition}},
  author    = {Zhao, Sanqiang and Gao, Yongsheng},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2009},
  pages     = {1629-1634},
  doi       = {10.1109/CVPR.2009.5206798},
  url       = {https://mlanthology.org/cvpr/2009/zhao2009cvpr-textural/}
}