• DocumentCode
    2951887
  • Title

    A driver fatigue recognition model using fusion of multiple features

  • Author

    Yang, G. ; Lin, Y. ; Bhattacharya, P.

  • Author_Institution
    Inst. for Inf. Syst. Eng., Concordia Univ., Montreal, Que., Canada
  • Volume
    2
  • fYear
    2005
  • fDate
    10-12 Oct. 2005
  • Firstpage
    1777
  • Abstract
    By using the fusion of contextual, visual and non-visual features, a model based on Dempster-Shafer (D-S) evidence theory is proposed to obtain a reliable driver´s fatigue recognition. Firstly, an overall model structure is set up with respect to the selected features and key symptoms of driver´s fatigue. Secondly, a set of heuristic knowledge rules are used to determine the basic probability assignment; and a modified evidence combination is adopted to combine multiple pieces of evidence including consistent and conflicting ones. Thirdly, decision policy based on the basic probability assignment is applied to fatigue recognition. At last, an example is given to illustrate the proposed fatigue recognition model.
  • Keywords
    driver information systems; emotion recognition; inference mechanisms; probability; uncertainty handling; Dempster-Shafer evidence theory; decision policy; driver fatigue recognition model; heuristic knowledge rule; multiple features fusion; probability assignment; Biomedical monitoring; Computer crashes; Electrocardiography; Electromyography; Emotion recognition; Fatigue; Frequency; Roads; Skin; US Department of Transportation; D-S evidence theory; Driver fatigue; contextual / physiological features; information fusion; recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2005 IEEE International Conference on
  • Print_ISBN
    0-7803-9298-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.2005.1571406
  • Filename
    1571406