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A HW/SW Co-Design Implementation of Viola-Jones Algorithm for Driver Drowsiness Detection

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Future Information Communication Technology and Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 235))

Abstract

There have been various recent methods proposed in detecting driver drowsiness (DD) to avert fatal accidents. This work proposes a hardware/software (HW/SW) co-design approach in implementation of a DD detection system adapted from the Viola-Jones algorithm to monitor driver’s eye closure rate. In this work, critical functions of the DD detection algorithm is accelerated through custom hardware components in order to speed up processing, while the software component implements the overall control and logical operations to achieve the complete functionality required of the DD detection algorithm. The HW/SW architecture was implemented on an Altera DE2 board with a video daughter board. Performance of the proposed implementation was evaluated and benchmarked against some recent works.

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References

  1. Wierwille WW, Ellsworth LA, Wreggit SS, Fairbanks RJ, Kirn CL (1994) Research on vehicle-based driver status/performance monitoring: development, validation, and refinement of algorithms for detection of driver drowsiness. National Highway Traffic Safety Administration, New Jersey

    Google Scholar 

  2. Betke M, Mullally WJ (2000) preliminary investigation of real-time monitoring of a driver in city traffic. Proceedings of the IEEE intelligent vehicles symposium, pp 563–568, IEEE, doi:10.1109/IVS.2000.898407

  3. D’Orazio T, Leo M, Guaragnella C, Distante A (2007) A visual approach for driver inattention detection. Pattern Recogn 40(8):2341–2355

    Article  MATH  Google Scholar 

  4. Wang F, Qin H (2005) A FPGA based driver drowsiness detecting system. IEEE international conference on vehicular electronics and safety, pp 358–363, IEEE, doi:10.1109/ICVES.2005.1563673

  5. Moreno F, Aparicio F, Hernandez W, Paez J (2003) A low-cost real-time FPGA solution for driver drowsiness detection. The 29th annual conference of the IEEE industrial electronics society, vol 2, pp 1396–1401, IEEE, doi:10.1109/IECON.2003.1280262

  6. Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. Proceedings of the IEEE computer society conference on computer vision and pattern recognition, vol 1, pp I-511–I-518, IEEE, doi:10.1109/CVPR.2001.990517

  7. Wei Y, Bing X, Chareonsak C (2004) FPGA implementation of AdaBoost algorithm for detection of face biometrics. IEEE international workshop on biomedical circuits and systems, pp S1/6- 17-20, IEEE, doi:10.1109/BIOCAS.2004.1454161

  8. Nair V, Laprise P, Clark J (2005) An FPGA-based people detection system. EURASIP J Appl Signal Process 2005(1):1047–1061, ACM Portal: ACM Digital Library

    Google Scholar 

  9. Hiromoto M, Nakahara K, Sugano H (2007) A specialized processor suitable for AdaBoost-based detection with haar-like features. IEEE conference on computer vision and pattern recognition, pp 1–8, IEEE, doi:10.1109/CVPR.2007.383415

  10. Lienhart R, Maydt J (2002) An extended set of haar-like features for rapid object detection. IEEE Intl Conf Image Process 1:900–903

    Article  Google Scholar 

  11. Open Source Computer Vision Library (2008) Intel Corporation, Santa Clara

    Google Scholar 

  12. Freund Y, Schapire RE (1995) A decision-theoretic generalization of on-line learning and an application to boosting. Computational learning theory: Eurocolt. Springer, pp 23–37

    Google Scholar 

  13. Grace R, Byrne VE, Bierman DM, Legrand JM, Gricourt D, Davis RK, Staszewski JJ, Carnahan B (1998) A drowsy driver detection system for heavy vehicles. Proceedings of the 17th DASC AIAA/IEEE/SAE digital avionics systems conference, vol 2, pp I36/1–I36/8, IEEE, doi:10.1109/DASC.1998.739878

  14. Veeraraghavan H, Papanikolopoulos N (2001) Detecting driver fatigue through the use of advanced face monitoring techniques. University of Minnesota, Minneapolis

    Google Scholar 

  15. Ji Q, Yang X (2002) Real-time eye, gaze, and face pose tracking for monitoring driver vigilance. Real Time Imaging 8:357–377

    Article  MATH  Google Scholar 

  16. Ji Q, Zhu Z, Lan P (2004) Real-time nonintrusive monitoring and prediction of driver fatigue. IEEE Trans Veh Technol 53(4):1052–1068, IEEE, doi:10.1109/TVT.2004.830974

  17. Cudalbu C, Anastasiu B, Radu R, Cruceanu R, Schmidt E, Barth E (2005) Driver monitoring with a single high-speed camera and IR illumination. International symposium on signals, circuits and systems, vol 1, pp 219–222, IEEE, doi:10.1109/ISSCS.2005.1509893

  18. Bergasa LM, Nuevo J, Sotelo MA, Vazquez M (2006) Real-time system for monitoring driver vigilance. IEEE Transp Intell Transport Syst 7(1):63–77, IEEE, doi:10.1109/TITS.2006.869598

    Google Scholar 

  19. Ebisawa Y, Satoh S (1993) Effectiveness of pupil area detection technique using two light sources and image difference method. Proceedings of the 15th annual international conference of the IEEE Engineering in Medicine and Biology Society, IEEE, pp 1268–1269

    Google Scholar 

  20. Ueno H, Kaneda M, Tsukino M (1994) Development of drowsiness detection system. Proceedings of the vehicle navigation and information systems conference, pp 15–20, IEEE, doi:10.1109/VNIS.1994.396873

  21. Sakaguchi Y, Nakano T, Yamamoto S (1996) Development of non-contact gaze detecting system and its applications to gaze duration measurement of on-board display. Proceedings of the IEEE intelligent vehicles symposium, IEEE, pp 289–294, IEEE, doi:10.1109/IVS.1996.566393

  22. Eriksson M, Papanikotopoulos NP (1997) Eye-tracking for detection of Driver fatigue. IEEE Conf Intell Transp Syst 9(12):314–319, IEEE, doi:10.1109/ITSC.1997.660494

    Google Scholar 

  23. Smith P, Shah M, da Vitoria Lobo N (2003) Determining driver visual attention with one camera. IEEE Trans Intell Transp Syst 4(4):205–218, IEEE, doi:10.1109/TITS.2003.821342

    Google Scholar 

  24. Wang R, Guo K, Shi S, Chu J (2003) A monitoring method of driver fatigue behavior based on machine vision. Proceedings of the intelligent vehicles Symposium, vol 9, no 11, pp 110–113, IEEE, doi:10.1109/IVS.2003.1212893

  25. Urtho (2007) Urtho’s face detection and normalization project, http://face.urtho.net/

  26. Kanade T, Cohn JF, Tian Y (2000) Comprehensive database for facial expression analysis. Proceedings of the fourth IEEE international conference on automatic face and gesture recognition (FG’00), Grenoble, pp 46–53

    Google Scholar 

  27. CVL face database http://www.lrv.fri.uni-lj.si/facedb.html

  28. Reimondo A (2008) Haar cascades, http://www.alereimondo.com.ar/OpenCV

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Correspondence to M. L. Dennis Wong .

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Lai, K.C., Dennis Wong, M.L., Islam, S.Z. (2013). A HW/SW Co-Design Implementation of Viola-Jones Algorithm for Driver Drowsiness Detection. In: Jung, HK., Kim, J., Sahama, T., Yang, CH. (eds) Future Information Communication Technology and Applications. Lecture Notes in Electrical Engineering, vol 235. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6516-0_46

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  • DOI: https://doi.org/10.1007/978-94-007-6516-0_46

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  • Online ISBN: 978-94-007-6516-0

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