• DocumentCode
    2725404
  • Title

    Part-Based Templet Matching in the Detection of Fatigue Driving

  • Author

    Gang Xu ; Xiaochen Liu ; Renzhe Li ; Lu Yang

  • Author_Institution
    Electr. & Electron. Eng. Sch., North China Electr. Power Univ., Beijing, China
  • fYear
    2012
  • fDate
    11-13 Aug. 2012
  • Firstpage
    2265
  • Lastpage
    2268
  • Abstract
    We describe a face detection system based on multiscale part models for drivers´ fatigue detection. Our system is able to represent human face using two eye areas and one mouth area. By using mulriple simple template instead of single template with complex details, new model observably improved the computational efficiency and veracity for face detection. This system also considers the specialty of fatigue detection and put out a new method for face detection for it. While color recognition is the most effective and simply method for face detection in conventional face detection. The specific application and condition decide the advantage of the model in the detection fatigue of drivers. To reflect the characteristic of the features of fatigued riving discriminant background, this paper uses an image with a complex background to simulate.
  • Keywords
    computer graphics; face recognition; image matching; image representation; object detection; traffic engineering computing; computational efficiency improvement; computational veracity improvement; computer graphics; drivers fatigue driving detection; face alignment; face detection system; face positioning problem; fatigued riving discriminant background; human face representation; part-based templet matching; Educational institutions; Face; Face detection; Fatigue; Humans; Image color analysis; Skin; drivers´ fatigue detection; face detection; multi-objects detecting; pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science & Service System (CSSS), 2012 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-0721-5
  • Type

    conf

  • DOI
    10.1109/CSSS.2012.562
  • Filename
    6394880