{
  "id": "1811.00116",
  "version": "v1",
  "published": "2018-10-31T20:58:39.000Z",
  "updated": "2018-10-31T20:58:39.000Z",
  "title": "Face Recognition: From Traditional to Deep Learning Methods",
  "authors": [
    "Daniel Sáez Trigueros",
    "Li Meng",
    "Margaret Hartnett"
  ],
  "categories": [
    "cs.CV"
  ],
  "abstract": "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 Traditional methods based on hand-crafted features and traditional machine learning techniques have recently been superseded by deep neural networks trained with very large datasets.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.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2018-10-31T20:58:39.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "deep learning methods",
      "popular face recognition methods",
      "up-to-date literature review",
      "traditional machine learning techniques",
      "deep neural networks"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}