Learning to Recognize Faces from Examples
Abstract
We describe an implemented system that learns to recognize human faces under varying pose and illumination conditions. The system relies on symmetry operations to detect the eyes and the mouth in a face image, uses the locations of these features to normalize the appearance of the face, performs simple but effective dimensionality reduction by a convolution with a set of Gaussian receptive fields, and subjects the vector of activities of the receptive fields to a Radial Basis Function interpolating classifier. The performance of the system compares favorably with the state of the art in machine recognition of faces.
Cite
Text
Edelman et al. "Learning to Recognize Faces from Examples." European Conference on Computer Vision, 1992. doi:10.1007/3-540-55426-2_89Markdown
[Edelman et al. "Learning to Recognize Faces from Examples." European Conference on Computer Vision, 1992.](https://mlanthology.org/eccv/1992/edelman1992eccv-learning/) doi:10.1007/3-540-55426-2_89BibTeX
@inproceedings{edelman1992eccv-learning,
title = {{Learning to Recognize Faces from Examples}},
author = {Edelman, Shimon and Reisfeld, Daniel and Yeshurun, Yehezkel},
booktitle = {European Conference on Computer Vision},
year = {1992},
pages = {787-791},
doi = {10.1007/3-540-55426-2_89},
url = {https://mlanthology.org/eccv/1992/edelman1992eccv-learning/}
}