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Survey on Driver’s Drowsiness Detection System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 132 - Number 5 |
| Year of Publication: 2015 |
| Authors: Omkar Dharmadhikari, Revati Bhor, Pranjal Mahajan, H.V. Kumbhar |
10.5120/ijca2015907349
|
Omkar Dharmadhikari, Revati Bhor, Pranjal Mahajan, H.V. Kumbhar . Survey on Driver’s Drowsiness Detection System. International Journal of Computer Applications. 132, 5 ( December 2015), 16-19. DOI=10.5120/ijca2015907349
Abstract
There is much attentional impairment while driving that affect driver’s reaction. Among which driving while drowsy is one of the major causes behind road accidents, and exposes the driver to a much higher crash risk compared to driving while alert. Therefore, the use of an assistive system that monitor a driver’s level of vigilance and alert the driver in case of drowsiness can be significant in the prevention of accidents. This paper introduces a new approach towards detection of driver's drowsiness based on yawning measurement and head movement. This involves several steps including the real time detection and tracking of driver’s face, detection and tracking of the mouth contour, the detection of yawning based on measuring both the rate and the amount of changes in the mouth contour area and head movement tracking. Test results demonstrate that the proposed system can efficiently measure the aforementioned parameters and detect driver’s drowsiness.
References
- S.G. Klauer , T. A. Dingus, Neale , V. L. , Sudweeks , J.D. , and Ramsey, DJ, ”The Impact of Driver Inattention on Near- Crash/Crash Risk: An Analysis Using the 100-Car Naturalistic Driving Study Data,” Virginia Tech Transportation Institute, Technical Report # DOT HS 810 594.
- W. Qiong, Y. Jingyu, R. Mingwu and Z. Yujie, "Driver Fatigue Detection: A Survey," The Sixth World Congress on Intelligent Control and Automation, vol. 2, pp. 8587-8591, 2006.
- Tuner, L. ven , F. Co kun and E. Karsl gil, Vision based lane keeping assistance control triggered by a driver inattention monitor," in IEEE International Conference on Systems Man and Cybernetics (SMC), Istanbul, 10-13 Oct. 2010
- T. Pilutti and A. Ulsoy, "Identification of driver state for lane-keeping tasks," IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, vol. 29, no. 5, pp. 486-502, 1999.
- A. Picot, S. Charbonnier and A. Caplier, "On-Line Detection of Drowsiness Using Brain and Visual Information," IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, no. 99, pp. 1-12, 2011.
- G. Furman, A. Baharav, C. Cahan and S. Akselrod, "Early detection of falling asleep at the wheel: A Heart Rate Variability approach," Computers in Cardiology, pp. 1109-1112, 2008.
- S. Hu and R. Bowlds, "Pulse wave sensor for non-intrusive driver's drowsiness detection," in Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE, Minneapolis, MN, 2009.
- K. Hayashi, K. Ishihara, H. Hashimoto and K. Oguri, "Individualized drowsiness detection during driving by pulse wave analysis with neural network," in Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, Austria , 2005.
- S. Sirohey, "Human Face Segmentation and Identification," in Technical Report CS-TR-3176, Maryland, 1993.
- H. Graf, T. Chen, E. Petajan and E. Cosatto, "Locating Faces and Facial Parts," in Proc. First Int’l Workshop Automatic Face and Gesture Recogniction, 1995.
- C. Han, H. Liao, K. Yu and L. Chen, "Fast Face Detection via Morphology-Based Pre-Processing," in Proc. Ninth Int’l Conf. Image Analysis and Processing, 1998.
- Y. Ying, S. Jing and Z. Wei, "The Monitoring Method of Driver's Fatigue Based on neural network," in International Conference on Mechatronics and Automation, 2007, Harbin, 2007.
- D. Saxe and R. Foulds, "Towards Robust Skin Identification in Video Images," in Proc. Second Int’l Conf. Automatic Face and Gesture Recognition, 1996.
- I. Craw, H. Ellis and J. Lishman, "Automatic Extraction of Face Features," Pattern Recognition Letters, vol. 5, pp. 183-187, 1987.
- X. Liu, G. Geng and X. Wang, "Automatically face detection based on BP neural network and Bayesian decision," in Sixth International Conference on Natural Computation (ICNC), Yantai, Shandong, 2010.
- X. Fan, B. Yin, Y. Fun. “Yawning Detection For Monitoring Driver Fatigue.” In: Proc. Sixth International Conf. on Machine Learning and Cybernetics, Hong Kong, 2007, pp. 664-668.
- T. Azim, M.A. Jaffar, A.M. Mirza. “Automatic Fatigue Detection of Drivers through Pupil Detection and Yawning Analysis.” In: Proc. Fourth International Conf. on Innovative Computing, Information and Control, 2009, pp. 441-445.
- T.Wang, P. Shi. “Yawning Detection For Determining Driver Drowsiness.” IEEE International Workshop VLSI Design & Video Tech. Suzhou
- M. Saradadevi and P. Bajaj, "Driver Fatigue Detection Using Mouth and Yawning Analysis," IJCSNS International Journal of Computer Science and Network Security, vol. 8, no. 6, pp. 183-188, June 2008.
- E. Vural, M. Cetin, A. Ercil, G. Littlewort , M. Barlett and J. Movellan, “Drowsy Driver Detection Through Facial Movement Analysis”.
- M. Sigari, "Driver Hypo-vigilance Detection Based on Eyelid Behavior," in Seventh International Conference on Advances in Pattern Recognition, 2009.
- D. Liu, P. Sun, Y. Xiao and Y. Yin, "Drowsiness Detection Based on Eyelid Movement," in 2010 Second International Workshop on Education Technology and Computer Science (ETCS), 2010.
- M. Omidyeganeh, A. Javadtalab and S. Shirmohammadi, "Intelligent driver drowsiness detection through fusion of yawning and eye closure," in IEEE International Conference on Virtual Environments Human-Computer Interfaces and Measurement Systems (VECIMS), 2011.
- P. Viola and M. Jones, "Robust real-time face detection," International Journal of Computer Vision , vol. 57, no. 2, pp. 137-154, 2001.
- L. Li, Y. Chen , Z. Li. “Yawning Detection for Monitoring Driver Fatigue Based on Two Cameras.” In: Proc. 12th International IEEE Conf. on Intelligent Transportation Systems, St. Louis, MO, USA, 2009, pp. 12-17.
- L. Li, Z. Li and Y. Chen, "Yawning detection for monitoring driver fatigue based on two cameras," in 12th International IEEE Conference on Intelligent Transportation Systems, 2009.
- X. Fan, B. Yin and Y. Sun, "Yawning Detection for Monitoring Driver Fatigue," in International Conference on Machine Learning and Cybernetics, 2007.
- R. Jimenez, F. Prieto and V. Grisales, "Detection of the Tiredness Level of Drivers Using Machine Vision Techniques”, Electronics, Robotics and Automotive Mechanics Conference, 2011.
- H. Selleahewa, S. Jassim, “Image-Quality-Based Adaptive Face Recognition “, IEEE Transaction on vol 59, no.4.
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