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
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