Abstract
Drowsiness and fatigue of automobile drivers reduce the drivers’ abilities of vehicle control, natural reflex, recognition and perception. Such diminished vigilance level of drivers is observed at night driving or overdriving, causing accident and pose severe threat to mankind and society. Therefore it is very much necessary in this recent trend in automobile industry to incorporate driver assistance system that can detect drowsiness and fatigue of the drivers. This paper presents a nonintrusive prototype computer vision system for monitoring a driver’s vigilance in realtime. Eye tracking is one of the key technologies for future driver assistance systems since human eyes contain much information about the driver’s condition such as gaze, attention level, and fatigue level. One problem common to many eye tracking methods proposed so far is their sensitivity to lighting condition change. This tends to significantly limit their scope for automotive applications. This paper describes real time eye detection and tracking method that works under variable and realistic lighting conditions. It is based on a hardware system for the real-time acquisition of a driver’s images using IR illuminator and the software implementation for monitoring eye that can avoid the accidents.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Elzohairy Y (2008) Fatal and injury fatigue-related crashes on ontario’s roads: a 5-year review. In: Working together to understand driver fatigue: report on symposium proceedings, february 2008
Dingus TA, Jahns SK, Horowitz AD, Knipling R (1998) Human factors design issues for crash avoidance systems. In: Barfield W, Dingus TA (eds) Human factors in intelligent transportation systems. Lawrence Associates, Mahwah, pp 55–93
Saito H, Ishiwaka T, Sakata M, Okabayashi S (1994) Applications of driver’s line of sight to automobiles—what can driver’s eye tell. In: Proceedings of vehicle navigation and information systems conference, Yokohama, Japan, pp 21–26
Ueno H, Kaneda M, Tsukino M (1994) Development of drowsiness detection system. In: Proceedings of vehicle navigation and information systems conference, Yokohama, Japan, pp 15–20
Boverie S, Leqellec JM, Hirl A (1998) Intelligent systems for video monitoring of vehicle cockpit. In: International Congress and exposition ITS: advanced controls and vehicle navigation systems, pp 1–5
Kaneda M et al (1994) Development of a drowsiness warning system. In: The 11th international conference on enhanced safety of vehicle, Munich
Onken R (1994) Daisy, an adaptive knowledge-based driver monitoring and warning system. In: Proceedings of vehicle navigation and information systems conference, Yokohama, Japan, pp 3–10
Feraric J, Kopf M, Onken R (1992) Statistical versus neural bet approach for driver behaviour description and adaptive warning. The 11th European annual manual, pp 429–436
Ishii T, Hirose M, Iwata H (1987) Automatic recognition of driver’s facial expression by image analysis. J Soc Automot Eng Jap 41:1398–1403
Yammamoto K, Higuchi S (1992) Development of a drowsiness warning system. J Soc Automot Eng Jap 46:127–133
Smith P, Shah M, da Vitoria Lobo N (2000) Monitoring head/eye motion for driver alertness with one camera. In: The 15th international conference on pattern recognition, vol 4, pp 636–642
Saito S (1992) Does fatigue exist in a quantitative of eye movement? Ergonomics 35:607–615
Anon (1999) Perclos and eye tracking: challenge and opportunity. Technical Report Applied Science Laboratories, Bedford
Wierville WW (1994) Overview of research on driver drowsiness definition and driver drowsiness detection. ESV, Munich
Dinges DF, Mallis M, Maislin G, Powell JW (1998) Evaluation of techniques for ocular measurement as an index of fatigue and the basis for alertness management. Dept Transp Highw Saf Publ 808:762
Anon (1998) Proximity array sensing system: head position monitor/metric. Advanced safety concepts, Inc., Sante Fe, NM87504
Anon (1999) Conference on ocular measures of driver alertness, Washington DC, April 1999
Qiang J, Xiaojie Y (2002) Real-Time Eye, Gaze, and face pose tracking for monitoring driver vigilance. Real-Time Imag 8:357–377
D’Orazio T, Leo M, Guaragnella C, Distante A (2007) A visual approach for driver inattention detection. Pattern Recogn 40(8):2341–2355
Boyraz P, Acar M, Kerr D (2008) Multi-sensor driver drowsiness monitoring. Proceedings of the institution of mechanical engineers, Part D: J Automobile Eng 222(11):2041–2062
Ebisawa Y (1989) Unconstrained pupil detection technique using two light sources and the image difference method. Vis Intell Des Eng, pp 79–89
Grauman K, Betke M, Gips J, Bradski GR (2001) Communication via eye blinks: detection and duration analysis in real time. In: Proceedings of IEEE conference on computer vision and pattern recognition, WIT Press, pp 1010–1017
Matsumoto Y, Zelinsky A (2000) An algorithm for real-time stereo vision Implementation of Head pose and gaze direction measurements. In: Proceedings of IEEE 4th international conference on face and gesture recognition, pp 499–505
Yuille AL, Hallinan PW, Cohen DS (1992) Feature extraction from faces using deformable templates. Int J Comput Vis 8(2):99–111
Ivins JP, Porrill J (1998) A deformable model of the human iris for measuring small 3-dimensional eye movements. Mach Vis Appl 11(1):42–51
Kawato S, Tetsutani N (2002) Real-time detection of between-the-eyes with a circle frequency filter. In: Asian conference on computer vision
Sommer G, Michaelis M, Herpers R (1998) The SVD approach for steerable filter design. In: Proceedings of international symposium on circuits and systems 1998, Monterey, California, vol 5, pp 349–353
Yang G, Waibel A (1996) A real-time face tracker. In: Workshop on applications of computer vision, pp 142–147
Loy G, Zelinsky A (2003) Fast radial symmetry transform for detecting points of interest. IEEE Trans Pattern Anal Mach Intell 25(8):959–973
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer India
About this paper
Cite this paper
Ghosh, S., Nandy, T., Manna, N. (2015). Real Time Eye Detection and Tracking Method for Driver Assistance System. In: Gupta, S., Bag, S., Ganguly, K., Sarkar, I., Biswas, P. (eds) Advancements of Medical Electronics. Lecture Notes in Bioengineering. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2256-9_2
Download citation
DOI: https://doi.org/10.1007/978-81-322-2256-9_2
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2255-2
Online ISBN: 978-81-322-2256-9
eBook Packages: EngineeringEngineering (R0)