{
  "id": "1504.05308",
  "version": "v1",
  "published": "2015-04-21T05:10:41.000Z",
  "updated": "2015-04-21T05:10:41.000Z",
  "title": "Automatic Face Recognition from Video",
  "authors": [
    "Ognjen Arandjelovic"
  ],
  "comment": "Doctor of Philosophy (PhD) dissertation, University of Cambridge, 2007",
  "categories": [
    "cs.CV"
  ],
  "abstract": "The objective of this work is to automatically recognize faces from video sequences in a realistic, unconstrained setup in which illumination conditions are extreme and greatly changing, viewpoint and user motion pattern have a wide variability, and video input is of low quality. At the centre of focus are face appearance manifolds: this thesis presents a significant advance of their understanding and application in the sphere of face recognition. The two main contributions are the Generic Shape-Illumination Manifold recognition algorithm and the Anisotropic Manifold Space clustering. The Generic Shape-Illumination Manifold is evaluated on a large data corpus acquired in real-world conditions and its performance is shown to greatly exceed that of state-of-the-art methods in the literature and the best performing commercial software. Empirical evaluation of the Anisotropic Manifold Space clustering on a popular situation comedy is also described with excellent preliminary results.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2015-04-21T05:10:41.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "automatic face recognition",
      "anisotropic manifold space clustering",
      "generic shape-illumination manifold recognition algorithm",
      "face appearance manifolds"
    ],
    "tags": [
      "dissertation"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2015arXiv150405308A"
    }
  }
}