Face identification by means of a neural net classifier
Computer Vision and Pattern Recognition
2022-04-04 v1 Cryptography and Security
Abstract
This paper describes a novel face identification method that combines the eigenfaces theory with the Neural Nets. We use the eigenfaces methodology in order to reduce the dimensionality of the input image, and a neural net classifier that performs the identification process. The method presented recognizes faces in the presence of variations in facial expression, facial details and lighting conditions. A recognition rate of more than 87% has been achieved, while the classical method of Turk and Pentland achieves a 75.5%.
Keywords
Cite
@article{arxiv.2204.00305,
title = {Face identification by means of a neural net classifier},
author = {Virginia Espinosa-Duro and Marcos Faundez-Zanuy},
journal= {arXiv preprint arXiv:2204.00305},
year = {2022}
}
Comments
5 pages, published in Proceedings IEEE 33rd Annual 1999 International Carnahan Conference on Security Technology (Cat. No.99CH36303) Madrid (Spain)