Research Article
Efficient Approach for Analyzing the Driver's Vigilance
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 114 - Issue 1 |
| Published: March 2015 |
| Authors: Belkacem Abbadi, Djamel Boubetra, Messaoud Mostefai |
10.5120/19940-1727
|
Belkacem Abbadi, Djamel Boubetra, Messaoud Mostefai . Efficient Approach for Analyzing the Driver's Vigilance. International Journal of Computer Applications. 114, 1 (March 2015), 7-10. DOI=10.5120/19940-1727
@article{ 10.5120/19940-1727,
author = { Belkacem Abbadi,Djamel Boubetra,Messaoud Mostefai },
title = { Efficient Approach for Analyzing the Driver's Vigilance },
journal = { International Journal of Computer Applications },
year = { 2015 },
volume = { 114 },
number = { 1 },
pages = { 7-10 },
doi = { 10.5120/19940-1727 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2015
%A Belkacem Abbadi
%A Djamel Boubetra
%A Messaoud Mostefai
%T Efficient Approach for Analyzing the Driver's Vigilance%T
%J International Journal of Computer Applications
%V 114
%N 1
%P 7-10
%R 10.5120/19940-1727
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Road accidents, due to the tiredness or the distraction of the drivers, unfortunately became more serious than a war. Although more or less effective solutions were developed to solve this problem, these last remain in general constraining and/or sensitive to the variations of lighting. This paper presents a new approach for analyzing the driver's vigilance based on motion analysis of an on-head reflecting point. Proposed solution is non-intrusive and easily adaptable to all types of vehicles. Moreover, developed tracking algorithm has a low computational complexity and is therefore well suited for a hardware implementation to suit real time driving constraints.
References
- Sahayadhas, A. , Sundaraj, K. , and Murugappan, M. 2012. Detecting Driver Drowsiness Based on Sensors: A Review. Sensors. 12 (Dec. 2012), 16937-16953.
- Kleinberger. T. , Jedlitschka, A. , Storf, H. , Steinbach-Nordmann, S. , and Prueckner, S. 2009. An approach to and evaluations of assisted living systems using ambient intelligence for emergency monitoring and prevention. In Proceedings of the 5th International Conference, UAHCI, Part II.
- Rakotonirainy, A. and Tay, R. 2004. In-vehicle ambient intelligent transport systems (i-vaits): Towards an integrated research. In Proceedings of the 7th international IEEE conference on intelligent transportation systems.
- Liu, C. C. , Hosking, S. G. , and Lenné, M. G. 2009. Predicting driver drowsiness using vehicle measures: Recent insights and future challenges. Journal of safety research. 40 (Aug. 2009), 239-245.
- Akin, M. , Kurt, M. , Sezgin, N. , and Bayram, M. 2008. Estimating vigilance level by using EEG and EMG signals. Neural Computing and Applications. 17 (June 2008), 227-236.
- Vitabile, S. , De Paola, A. , and Sorbello, F. 2011. A real-time non-intrusive FPGA-based drowsiness detection system. Journal of Ambient Intelligence and Humanized Computing. 2(Dec. 2011), 251-262.
- Jixu Chen, J. and Ji, Q. 2012. Drowsy Driver Posture, Facial, and Eye Monitoring Methods. In Handbook of Intelligent Vehicles, Eskandarian, A.
- Smith, P. , Shah, M. , and Vitoria, L. N. 2003. Determining driver visual attention with one camera. IEEE Trans. Intell. Transport. Syst. 4 (Dec. 2003), 205-218.
- Hemadri, V. B. and Umakant, P. K. 2013. Detection of Drowsiness Using Fusion of Yawning and Eyelid Movements. In Proceedings of the Third International Conference, ICAC3.
- Alioua, N. , Amine, A. , Rziza, M. , and Aboutajdine, D. 2011. Driver's Fatigue and Drowsiness Detection to Reduce Traffic Accidents on Road. In Proceedings of the 14th International Conference, CAIP, Part II.
- Choong Lai, K. , Wong, M. L. D. , and Islam, S. Z. 2013. A HW/SW Co-Design Implementation of Viola-Jones Algorithm for Driver Drowsiness Detection. In Future Information Communication Technology and Applications. Lecture Notes in Electrical Engineering Volume 235, Jung, H. K. , Kim, J. T. , Sahama, T. , Yang, C. H.
- Flores, M. J. , Armingol, J. M. , and De La Escalera, A. 2010. Real-Time Warning System for Driver Drowsiness Detection Using Visual Information. Journal of Intelligent & Robotic Systems. 59(Aug. 2010), 103-125.
- Vural, E. , Cetin, M. , Ercil, A. L. , Gwen, Bartlett, M. , and Movellan, J. 2007. Drowsy Driver Detection Through Facial Movement Analysis. In Proceedings IEEE International Workshop, HCI.
- Akrout, B. and Mahdi, W. 2013. Vision Based Approach for Driver Drowsiness Detection Based on 3D Head Orientation. In Multimedia and Ubiquitous Engineering, MUE 2013, Park, J. J. , Kee-Yin Ng, J. , Jeong, H. Y. , Waluyo, B.
- Lee, D. , Oh, S. , Heo, S. , and Hahn, M. 2008. Drowsy Driving Detection Based on the Driver's Head Movement using Infrared Sensors. In 2nd International Symposium on Universal Communication (ISUC '08).
- Barr, L. , Popkin, S. , and Howarth, H. 2009. An Evaluation of Emerging Driver Fatigue Detection Measures and Technologies. Technical Report. U. S Department of Transportation.
- J, Q. , Lan, P. and Zhu, Z. 2004. Real-time non-intrusive monitoring and prediction of driver fatigue. IEEE Transactions on Vehicular Technology. 53(July 2004), 1052-1068.
Index Terms
Keywords