Starting in the seventies, face recognition has become one of the most researched topics in computer vision and biometrics. Traditional methods based on hand-crafted features and traditional machine learning techniques have recently been superseded by deep neural networks trained with very large datasets. In this paper we provide a comprehensive and up-to-date literature review of popular face recognition methods including both traditional (geometry-based, holistic, feature-based and hybrid methods) and deep learning methods.
@article{arxiv.1811.00116,
title = {Face Recognition: From Traditional to Deep Learning Methods},
author = {Daniel Sáez Trigueros and Li Meng and Margaret Hartnett},
journal= {arXiv preprint arXiv:1811.00116},
year = {2018}
}