Presenting a model for dynamic facial expression changes in detecting drivers’ drowsiness
Keywords:
Automobile driving, Drowsiness, Facial expression, Image processingAbstract
Drowsiness while driving is a major cause of accidents. A driver fatigue detection system that is designed to sound an alarm, when appropriate, can prevent many accidents that sometime leads to the loss of life and property. In this paper, we classify drowsiness detection sensors and their strong and weak points. A compound model is proposed that uses image processing techniques to study the dynamic changes of the face to recognize drowsiness during driving.
References
Rau PS. NHTSA's drowsy driver research program fact sheet; Washington, DC: National Highway Traffic
Safety Administration. 1996.
Faber, J. "Detection of different levels of vigilance by eeg pseudo spectra". Neural Network World. 2004;
: 285-90.
Knipling RR, Wang JS. Crashes and fatalities related to driver drowsiness/fatigue. US Department of
Transportation, National Highway Traffic Safety Administration, Office of Crash Avoidance Research,
Research & Development. [Internet]: (1994). Available from: ntl.bts.gov/lib/jpodocs/repts_te/1004.pdf
Dinges DF. Mallis MM. Managing fatigue by drowsiness detection: Can technological promises be
realized? WESTERN AUSTRALIA; In INTERNATIONAL CONFERENCE ON FATIGUE AND
TRANSPORTATION, 3RD; FREMANTLE; [Internet]: (1998). Available from:
http://trid.trb.org/view.aspx?id=539294
Wang JS, Knipling RR. Blincco LJ. Motor vehicle crash in volvements: A multi-dimensional problem size
assessments. ITS America Sixth Annual Meeting; Intelligent Transportation: Realizing the Benefits
Houston, Texas, 1996 April, 15-18. Available from:
ntl.bts.gov/lib/16000/16400/16472/PB2000104014.pdf
DETR. ”Tomorrow’s Roads” - Safer for Everyone, Department of the Environment, Transport and the
Regions, 2000. 7) “Driver Fatigue, Problem Definition and Countermeasure Summary”. Roads and Traffic Authority (RTA)
of New South Wales; (Dec 2001). Available from: http://www.rta.nsw.gov.au/
SekoY. “Present Technological Status of Detecting Drowsy Driving Patterns“.Central Research Institute,
Nissan Motor Company: JidoshaGijutsu, 1984; 30(5), 547-54.
Tilley, D, Erwin C, and Gianturco D. Drowsiness and driving: preliminary report of a population survey.
SAE International Automotive Engineering Congress, Detroit, Report No.730121,1973,
DOI:10.4271/730121
Planque S , Petit C , and Chapeau D , “ A System for Identifying Lapses of Alertness When Driving “ ;
Renault ;1991 . 11) Eskandarian A. and Sayed R. A, “Analysis of Driver Impairment, Fatigue, and Drowsiness and an
Unobtrusive Vehicle-Based Detection Scheme“, First International Conference on Traffic Accidents,
Tehran. [Internet]. Available from:
http://www.researchgate.net/publication/228964508_Analysis_of_Driver_Impairment_Fatigue_and_Drows
iness_and_an_Unobtrusive_Vehicle-Based_Detection_Scheme
Bergasa LM, Nuevo JU, Sotelo MA, Barea R, Lopez E. Visual Monitoring of Driver Inattention; 2008
Nov; Studies in Computational Intelligence (SCI); 8-17.
Ayati E. Drowsiness and fatigue. The most frequent causes of severe accidents among heavy vehicle
drivers in Iran ; (2004) ; Nottingham ; International Conference on Traffic & Transport Psychology ;
(2004). [Internet]. Available from: http://www. psychology.nottingham.ac.uk,
http://profdoc.um.ac.ir/articles/a/102198.pdf
Unicef org [Internet]: Road Traffic Injuries in Iran and their Prevention, A Worrying Picture. Available
from: http://www.unicef.org/iran/media_4783.html
Iran Legal Medicine Organization [Internet]. "Road Safety Commission, Necrology and injuries resulting
from traffic accidents Referred to Legal Medicine Center of Iran in 2011" Available from:
http://www.lmo.ir/uploads/1_26_92_tasp_9012.pdf [Text in Persian]
Hargutt V, Hoffmann S, Vollrath M, Krüger HP. Compensation for drowsiness & fatigue - a driving
simulation study. (2000); Bern, Switzerland ; In : Proceedings of the International Conference on
Traffic and Transport Psychology ICTTP , 4-7 September (2000).
Arun S, Kenneth S, Murugappan M. Detecting Driver Drowsiness Based on Sensors: A Review. Sensors
; 12(12):16937-53. doi:10.3390/s121216937
Khan MI, Mansoor AB. Real Time Eyes Tracking and Classification for Driver Fatigue Detection (ICIAR);
Springer; Verlag Berlin Heidelberg. LNCS 5112. 729-738, DOI: 10.1007/978-3-540-69812-8_72
Dong W, Wu X. Driver Fatigue Detection Based on the Distance of Eyelid. IEEE Int, 2005; Workshop
VLSI Design & Video Tech Suzhou China. 28911:11. DOI:10.1109/IWVDVT.2005.1504626
Ryan WJ, Duchowski AT, Birchfield ST. Limbus / Pupil, Switching For Wearable Eye Tracking Under
Variable Lighting Conditions. ETRA, Proceedings of the 2008 symposium on Eye tracking research &
applications, 61-4 Doi:10.1145/1344471.1344487.
Published
Issue
Section
License
Copyright (c) 2020 KNOWLEDGE KINGDOM PUBLISHING
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
