ML Anthology

Face Verification Using Error Correcting Output Codes

Josef Kittler, Reza Ghaderi, Terry Windeatt, Jiri Matas
CVPR 2001 pp. I:755-760
doi:10.1109/CVPR.2001.990552 /cvpr/2001/kittler2001cvpr-face/

Abstract

The error correcting output coding (ECOC) approach to classifier design decomposes a multi-class problem into a set of complementary two-class problems. We show how to apply the ECOC concept to automatic face verification, which is inherently a two-class problem. The output of the binary classifiers defines the ECOC feature space, in which it is easier to separate transformed patterns representing clients and impostors. We propose two different combining strategies as the matching score for face verification. The first uses the first order Minkowski metric, and requires a threshold to be set. The second is a kernel-based method and has no parameters to set. The proposed method exhibits better performance on the well known XM2VTS data set compared with previous reported results.

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Text

Kittler et al. "Face Verification Using Error Correcting Output Codes." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001. doi:10.1109/CVPR.2001.990552

Markdown

[Kittler et al. "Face Verification Using Error Correcting Output Codes." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001.](https://mlanthology.org/cvpr/2001/kittler2001cvpr-face/) doi:10.1109/CVPR.2001.990552

BibTeX

@inproceedings{kittler2001cvpr-face,
  title     = {{Face Verification Using Error Correcting Output Codes}},
  author    = {Kittler, Josef and Ghaderi, Reza and Windeatt, Terry and Matas, Jiri},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2001},
  pages     = {I:755-760},
  doi       = {10.1109/CVPR.2001.990552},
  url       = {https://mlanthology.org/cvpr/2001/kittler2001cvpr-face/}
}