Which Parts of the Face Give Out Your Identity?

Omar Ocegueda, Shishir K. Shah, Ioannis A. Kakadiaris

CVPR 2011 pp. 641-648

doi:10.1109/CVPR.2011.5995613 /cvpr/2011/ocegueda2011cvpr-parts/

Abstract

We present a Markov Random Field model for the analysis of lattices (e.g., images or 3D meshes) in terms of the discriminative information of their vertices. The proposed method provides a measure field that estimates the probability of each vertex to be “discriminative” or “non-discriminative”. As an application of the proposed framework, we present a method for the selection of compact and robust features for 3D face recognition. The resulting signature consists of 360 coefficients, based on which we are able to build a classifier yielding better recognition rates than currently reported in the literature. The main contribution of this work lies in the development of a novel framework for feature selection in scenarios in which the most discriminative information is known to be concentrated along piece-wise smooth regions of a lattice.

CVPR Semantic Scholar

Cite

Text

Ocegueda et al. "Which Parts of the Face Give Out Your Identity?." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2011. doi:10.1109/CVPR.2011.5995613

Markdown

[Ocegueda et al. "Which Parts of the Face Give Out Your Identity?." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2011.](https://mlanthology.org/cvpr/2011/ocegueda2011cvpr-parts/) doi:10.1109/CVPR.2011.5995613

BibTeX

@inproceedings{ocegueda2011cvpr-parts,
  title     = {{Which Parts of the Face Give Out Your Identity?}},
  author    = {Ocegueda, Omar and Shah, Shishir K. and Kakadiaris, Ioannis A.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2011},
  pages     = {641-648},
  doi       = {10.1109/CVPR.2011.5995613},
  url       = {https://mlanthology.org/cvpr/2011/ocegueda2011cvpr-parts/}
}