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
Link To Document :
بازگشت