On driver eye closure recognition for commercial vehicles

SAE Technical Papers

Volumn , Issue , 2008, Pages

  Hammoud, Riad I ^a   Witt, Gerald ^a   Dufour, Robert ^a   Wilhelm, Andrew ^a   Newman, Timothy ^a  

^a DELPHI CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMOBILES; AUTOMOTIVE ENGINEERING;

BUILDING BLOCKES; DRIVER DROWSINESS; DRIVING CONDITIONS; EYE CLOSURE RECOGNITION; EYE LOCATION; EYE MONITORING; IN-DEPTH ANALYSIS; OPERATIONAL TEST;

COMMERCIAL VEHICLES;

EID: 85072457660     PISSN: 01487191     EISSN: 26883627     Source Type: Journal    
DOI: 10.4271/2008-01-2691     Document Type: Conference Paper

References (32)

1. Bergasa L. M., Nuevo J., Sotelo M. A., Barea R., and Lopez M. E.,. Real-time system for monitoring driver vigilance. IEEE Transactions on Intelligent Transportation Systems, 7 (1): 63. 77, 2006. 2
2. Bueker U., Schmidt R., and Wiesner S.,. Camera-based driver monitoring for increased safety and convenience. In SAE Int'l Conf., IVI Technology and Intelligent Transportation Systems (SP-2099), 2007World Congress Detroit, Michigan, April 16-19 2007.2
3. Campbell B. N., Smith J. D., and Najm W. G.,. Examination of crash contributing factors using national crash databases. Technical report, The Volpe National Transportation Systems Center, April 2002. 1
4. Chang J., Cho C., and Lu S.,. A fuzzy integral based information fusion for drowsiness detection. International Journal of Fuzzy Systems, 7 (2): 63. 70, June 2005. 2
5. Dinges D. F., Mallis M. M., Maislin G., and Powell J. W.,. Evaluation of techniques for ocular measurement as an index of fatigue and the basis for alertness management. Technical report, National Highway Traffic Safety Administration, 1998. 1, 2
6. Driskell J. E., and Mullen B.,. The ef-cacy of naps as a fatigue countermeasures: a meta-analytic integration. Human Factors, 47: 360. 377, 2005. 4
7. Eby D. W., and Kostyniuk L. P.,. Safety vehicles using adaptive interface technology (task 1): Distracted-driving scenarios: A synthesis of literature, 2001 crashworthiness data system (cds) data, and expert feedback. Technical report, University of Michigan Transportation Research Institute, 2004.1
8. Erwin C. W.,. Studies of drowsiness (-nal report). Technical report, Durham, NC: The National Driving Center, Durham, NC, 1976. 1, 2
9. Fairbanks R. J., Fahey S. E., and Wierwille W. W.,. Research on vehicle-based driver status/performance monitoring: Seventh semi-annual research report. Technical report, National Highway Traf-c Safety Administration, 1995. 1, 2
10. Fell D.,. Safety update: problem de-nition and countermeasure summary: Fatigue. Technical report, New South Wales Road Safey Bureau, Australia, 1994.1
11. Eye-activity measures of fatigue and napping as a fatigue countermeasure, 1999. 4
12. Golz M., Sommer D., Chen M., Trutschel U., and Mandic D.,. Feature fusion for the detection of microsleep events. Signal Processing Systems for Signal, Image, and Video Technology. Special Issue: Data Fusion for Medical, Industrial, and Environmental Applications (Eds.: Mandic D., and Obradovic D.,), 49 (2): 329. 342, November 2007. 2
13. Hammoud R. I., and Hansen D.W.,. Physics of the Automatic Target Recognition (by Sadjadi F., (Ed)), chapter Biophysics of the eye in computer vision: methods and advanced technologies. Springer-Verlag, 2007. 4
14. Hammoud R. I., Wilhelm A., Malawey P., and Witt G. J.,. Efficient real-time algorithms for eye state and head pose tracking in advanced driver support systems. In CVPR '05: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)-Volume 2, page 1181, Washington, DC, USA, 2005. IEEE Computer Society. 4
15. Hammoud R. I., and Zhang H.,. Passive Eye Monitoring: Algorithms, Applications and Experiments (by, Hammoud Riad I.,), chapter Alertometer: Detecting and Mitigating Driver Drowsiness and Fatigue Using an Integrated Human Factors and Computer Vision Approach, pages 300. 320. Signals and Communication Technology. Springer, xviii, 481 p. 180 illus., 79 in color., hardcover edition, 2008. ISBN: 978-3-540-75411-4. 1, 2
16. Hansen D. W., and Hammoud R. I.,. An improved likelihood model for eye tracking. Computer Vision and Image Understanding, 106 (2-3): 220. 230, 2007. ISSN: 1077-3142. 4
17. Hayashi K., Ishihara K., and Hashimoto K., H., and Oguri,. Individualized drowsiness detection during driving by pulse wave analysis with neural network. In IEEE Conference on Intelligent Transportation Systems, pages 901. 906, 2005. 2
18. Horne J. A., and Reyner L. A.,. Sleep-related vehicle accidents. British Medical Journal, 310: 565. 567, 1995. 1
19. Hussain A., Bais B., Samad S., and Farshad Hendi S.,. Novel data fusion approach for drowsiness detection. Information Technology Journal, 7 (1): 48. 55, 2008. 2
20. Ji Q., Zhu Z., and Lan P.,. Real-time nonintrusive monitoring and prediction of driver fatigue. IEEE Transactions on Vehicular Technology, 53 (4): 1052. 1068, 2004. 2
21. Klauer S. G., Dingus T. A., Neele V. L., Sudweeks J. D., and Rasey D. J.,. The impact of driver inattention on nearcrash crash risk: An analysis using the 100-car naturalistic driving study data. Technical report, Virginia Tech Transportation Institute, 2006. 1
22. Knipling P. R., and Wang S. S.,. Revised estimates of the us drowsy driver crash problem size based on general estimates system case reviews. In 39th Annual Proceedings, Association for the Advancement of Automotive Medicinea, Chicago, 1995. 1
23. Kozak K., Pohl J., Birk W., Greenberg J., Artz B., Blommer M., Cathey L., and Curry R.,. Evaluatoin of lane departure warnings for drowsy drivers. In Proceedings of the human factors society 50th annual meeting, pages 2400. 2404, San Francisco, CA, 2006. 4
24. Lin C., Wu R., Liang S., Chao W., Chen Y., and Jung T.,. Eeg-based drowsiness estimation for safety driving using independent component analysis. IEEE Trans. on Circuits and Systems, 52 (12), 2005. 1
25. Nakano T., Sugiyama K., Mizuno M., and Yamamoto S.,. Blink measurement by image processing and application to warning of driver's drowsiness in automobiles. In IEEE Intelligent Vehicles, 1998. 2
26. Orden K. F. V., Jung T. P., and Makeig S.,. Combined eye activity measures accurately estimate changes in sustained visual task performance. Biological Psychology, 52: 221. 240, 2000. 1
27. Papadelis C., Kourtidou-Papadeli C., Bamidis P., Chouvarda I., Koufogiannis D., E. Bekiaris, and Maglaveras N.,. Indicators of sleepiness in an ambulatory eeg study of night driving. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006. 1
28. Park I., Ahn J., and Byun H.,. Ef-cient measurement of the eye blinking by using decision function for intelligent vehicles. In 7th International Conference on Computational Science (ICCS'07), pages 546. 549, 2007. 2
29. Rau P. S.,. Drowsy driver detection and warning system for commercial vehicle drivers: Field operational test design, data analysis, and progress. In 19th International Technical Conference on the Enhanced Safety of Vehicles (CD)., Washington, DC, 2005. 2
30. Royal D.,. Volume i: Findings: National survey of distracted and drowsy driving attitudes and behavior: 2002. Technical report, The Gallup Organization, 2003. 1
31. Sanquist T. F., and McCallum M. C.,. A review, evaluation and classification of fatigue countermeasures for transportation operators. In Proceedings of the Human Factors and Ergonomics Society 48th Annual Meeting, Santa Monica, CA, 2004. 4
32. Sirevaag E. J., and Stern J. A.,. Engineering psychophysiology: Issues and applications., chapter Ocular measures of fatigue and cognitive factors. Lawrence Erlbaum and Associates, Inc., Mahwah, NJ, backs r. w., and boucsein w., (eds) edition, 2000. 1