{
  "id": "1009.5758",
  "version": "v1",
  "published": "2010-09-29T03:13:09.000Z",
  "updated": "2010-09-29T03:13:09.000Z",
  "title": "Face Detection with Effective Feature Extraction",
  "authors": [
    "Sakrapee Paisitkriangkrai",
    "Chunhua Shen",
    "Jian Zhang"
  ],
  "comment": "7 pages. Conference version published in Asian Conf. Comp. Vision 2010",
  "categories": [
    "cs.CV"
  ],
  "abstract": "There is an abundant literature on face detection due to its important role in many vision applications. Since Viola and Jones proposed the first real-time AdaBoost based face detector, Haar-like features have been adopted as the method of choice for frontal face detection. In this work, we show that simple features other than Haar-like features can also be applied for training an effective face detector. Since, single feature is not discriminative enough to separate faces from difficult non-faces, we further improve the generalization performance of our simple features by introducing feature co-occurrences. We demonstrate that our proposed features yield a performance improvement compared to Haar-like features. In addition, our findings indicate that features play a crucial role in the ability of the system to generalize.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2010-09-29T03:13:09.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "effective feature extraction",
      "haar-like features",
      "face detector",
      "simple features",
      "first real-time adaboost"
    ],
    "tags": [
      "conference paper"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 7,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2010arXiv1009.5758P"
    }
  }
}