Survey of Biometric Techniques for Automotive Applications

  • Maria Villa
  • Mikhail GofmanEmail author
  • Sinjini Mitra
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 738)


Although significant research has been dedicated to developing biometric solutions for motorized vehicles, there are currently no survey works charting the progress in this field. This paper discusses a selection of biometrics research focusing on improving vehicle safety and protecting vehicles against theft. Specifically, we discuss research that focuses on detecting a driver’s impaired ability to control the vehicle due to drowsiness, intoxication, or a medical emergency; developing techniques for identifying and preventing intrusions into the vehicle; and discovering driver distractions from within and without the vehicle. We also comment on the potential effectiveness, user-friendliness, privacy, security, and other aspects of the proposed approaches and identify directions for future research.

We supplement this paper with a comprehensive list of other works in the field, which is accessible from Gofman and Villa (Extended database of biometrics research for automotive applications, 2017.


Biometrics Machine learning Vehicles Automotive Transportation 


  1. 1.
  2. 2.
    J. Adell, P. Jodrá, Exact kolmogorov and total variation distances between some familiar discrete distributions. J. Inequal. Appl. 2006(1), 64307 (2006)Google Scholar
  3. 3.
    F. Althoff, R. Lindl, L. Walchshausl, S. Hoch, Robust multimodal hand-and head gesture recognition for controlling automotive infotainment systems. VDI BERICHTE 1919, 187 (2005)Google Scholar
  4. 4.
  5. 5.
  6. 6.
    P.N. Belhumeur, J.P. Hespanha, D.J. Kriegman, Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 711–720 (1997)Google Scholar
  7. 7.
    S. Ben-Yacoub, B. Fasel, Fast Multi-Scale Face Detection (IDIAP, Martigny, 1998)Google Scholar
  8. 8.
    M. Billinghurst, B. Buxton, Gesture based interaction, in Haptic Input, 24 (2011)Google Scholar
  9. 9.
    K.W. Bowyer, K. Chang, P. Flynn, A survey of approaches and challenges in 3D and multi-modal 3D+ 2D face recognition. Comput. Vis. Image Underst. 101(1), 1–15 (2006)Google Scholar
  10. 10.
  11. 11.
    R. Chen, M. She, J. Wang, X. Sun, L. Kong, Driver verification based on handgrip recognition on steering wheel, in 2011 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (IEEE, New York, 2011), pp. 1645–1651Google Scholar
  12. 12.
    X. Chen, P.J. Flynn, K.W. Bowyer, PCA-based face recognition in infrared imagery: baseline and comparative studies, in IEEE International Workshop on Analysis and Modeling of Faces and Gestures, AMFG 2003 (IEEE, New York, 2003), pp. 127–134Google Scholar
  13. 13.
    O. Dehzangi, C. Williams, Towards multi-modal wearable driver monitoring: impact of road condition on driver distraction, in 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) (IEEE, New York, 2015), pp. 1–6Google Scholar
  14. 14.
    C. Endres, T. Schwartz, C.A. Müller, Geremin: 2D microgestures for drivers based on electric field sensing, in Proceedings of the 16th International Conference on Intelligent User Interfaces (ACM, New York, 2011), pp. 327–330Google Scholar
  15. 15.
    C.O. Folorunso, L.A. Akinyemi, A.A. Ajasa, K. Oladipupo, Design and development of fingerprint based car starting system presentation made at 16th International Conference on Electronic Packaging Technology (ICEPT 2015), Exhibition on Power and Telecommunications, Development_of_Fingerprint_based_Car_Starting_System_(Folorunsho_ C_et_al.pdf
  16. 16.
    Y. Freund, R.E. Schapire, A desicion-theoretic generalization of on-line learning and an application to boosting, in European Conference on Computational Learning Theory (Springer, Berlin, 1995), pp. 23–37Google Scholar
  17. 17.
    Future jaguar cars may recognize approaching drivers (2016).
  18. 18.
    Gestigon, The future of mobility is not about cars.
  19. 19.
    M. Gofman, M. Villa, Extended database of biometrics research for automotive applications. (2017)
  20. 20.
    M. Gutmann, P. Grausberg, K. Kyamakya, Detecting human driver’s physiological stress and emotions using sophisticated one-person cockpit vehicle simulator, in Information Technologies in Innovation Business Conference (ITIB) (IEEE, New York, 2015), pp. 15–18Google Scholar
  21. 21.
    K. Igarashi, C. Miyajima, K. Itou, K. Takeda, F. Itakura, H. Abut, Biometric identification using driving behavioral signals, in 2004 IEEE International Conference on Multimedia and Expo, 2004. ICME’04, vol. 1 (IEEE, New York, 2004), pp. 65–68Google Scholar
  22. 22.
    K.A. Ishak, S.A. Samad, A. Hussain, A face detection and recognition system for intelligent vehicles. Inf. Technol. J. 5(3), 507–515 (2006)Google Scholar
  23. 23.
    R. Ivers, T. Senserrick, S. Boufous, M. Stevenson, H.-Y. Chen, M. Woodward, R. Norton, Novice drivers’ risky driving behavior, risk perception, and crash risk findings from the drive study (2009).
  24. 24.
    Jaguar files patent for vehicle access system with facial recognition and gait analysis (2016).
  25. 25.
    J.B. Jadav, K.H. Wandra, R. Dabhi, Innovative automobile security system using various security modules, International Journal of Scientific Progress and Research 8(1), 24–27Google Scholar
  26. 26.
    J. Kang, D.V. Anderson, M.H. Hayes, Face recognition in vehicles with near infrared frame differencing, in IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE) (IEEE, New York, 2015), pp. 358–363Google Scholar
  27. 27.
    N. Kiruthiga, S. Thangasamy, et al., Real time biometrics based vehicle security system with GPS and GSM technology. Proc. Comput. Sci. 47, 471–479 (2015)Google Scholar
  28. 28.
    S.K. Kopparapu, A robust speech biometric system for vehicle access, in 2009 IEEE International Conference on Vehicular Electronics and Safety (ICVES) (IEEE, New York, 2009), pp. 174–177Google Scholar
  29. 29.
    H.B. Lee, J.M. Choi, J.S. Kim, Y.S. Kim, H.J. Baek, M.S. Ryu, R.H. Sohn, K.S. Park, Nonintrusive biosignal measurement system in a vehicle, in 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2007 (IEEE, New York, 2007), pp. 2303–2306Google Scholar
  30. 30.
    J. Lee, Omron integrating facial recognition into autonomous driving system (2016).
  31. 31.
    A. Leonardis, H. Bischof, Dealing with occlusions in the eigenspace approach, in 1996 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1996. Proceedings CVPR’96 (IEEE, New York, 1996), pp. 453–458Google Scholar
  32. 32.
    libfprint API reference.
  33. 33.
    Z. Liu, A new embedded car theft detection system, in Second International Conference Onembedded Software and Systems, 2005 (IEEE, New York, 2005), 6 pp.Google Scholar
  34. 34.
    Z. Liu, G. He, Research on vehicle anti-theft and alarm system using facing recognition, in International Conference on Neural Networks and Brain, 2005. ICNN&B’05, vol. 2 (IEEE, New York, 2005), pp. 925–929Google Scholar
  35. 35.
    C. Lupu, V. Lupu, Multimodal biometrics for access control in an intelligent car, in International Symposium on Computational Intelligence and Intelligent Informatics, 2007. ISCIII’07 (IEEE, New York, 2007), pp. 261–267Google Scholar
  36. 36.
    I.D. Markwood, Y. Liu, Vehicle self-surveillance: sensor-enabled automatic driver recognition, in Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security (ACM, New York, 2016), pp. 425–436Google Scholar
  37. 37.
    S. Mayhew, Ford granted patent for keyless biometric system for vehicles (2015).
  38. 38.
    A. Meschtscherjakov, H. Scharfetter, S.P. Kernjak, N.M. Kratzer, J. Stadon, Adaptive digital sunshade: blocking the sun from blinding the driver, in Adjunct Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (ACM, New York, 2015), pp. 78–83Google Scholar
  39. 39.
    Mobile ID World, Keeping drivers safe with pupil biometrics (2016).
  40. 40.
    National Highway Traffic Safety Administration et al., Early estimate of motor vehicle traffic fatalities for the first 9 months of 2016 (2017).
  41. 41.
    NHTSA, Contribution of medical conditions to passenger vehicle crashes (2009).
  42. 42.
  43. 43.
    D. Nosowitz, A car seat that authenticates the driver with butt recognition (2011).
  44. 44.
    O. Omeni, A.C. Wai Wong, A.J. Burdett, C. Toumazou, Energy efficient medium access protocol for wireless medical body area sensor networks. IEEE Trans. Biomed. Circuits Syst. 2(4), 251–259 (2008)CrossRefGoogle Scholar
  45. 45.
    M. Oravec, J. Pavlovicova, Face recognition methods based on principal component analysis and feedforward neural networks, in Proceedings of 2004 IEEE International Joint Conference on Neural Networks, vol. 1 (IEEE, New York, 2004), pp. 437–441Google Scholar
  46. 46.
    S. Padmapriya, E.A. KalaJames, Real time smart car lock security system using face detection and recognition, in International Conference on Computer Communication and Informatics (ICCCI) (IEEE, New York, 2012), pp. 1–6Google Scholar
  47. 47.
    A. Pentland, B. Moghaddam, T. Starner, et al., View-based and modular eigenspaces for face recognition, in CVPR, vol. 94 (1994), pp. 84–91Google Scholar
  48. 48.
    R. Rathore, C. Gau, Integrating biometric sensors into automotive internet of things, in International Conference on Cloud Computing and Internet of Things (CCIOT) (2014), pp. 178–181Google Scholar
  49. 49.
    A. Reyes-Muñoz, M.C. Domingo, M.A. López-Trinidad, J.L. Delgado, Integration of body sensor networks and vehicular ad-hoc networks for traffic safety. Sensors 16(1), 107 (2016)Google Scholar
  50. 50.
    H.A. Rowley, S. Baluja, T. Kanade, Human face detection in visual scenes, in Advances in Neural Information Processing Systems (1996), pp. 875–881Google Scholar
  51. 51.
    H. Samet, The quadtree and related hierarchical data structures. ACM Comput. Surv.(CSUR) 16(2), 187–260 (1984)Google Scholar
  52. 52.
    Sense holdings acquires exclusive sales, marketing and purchase rights for biometric patent to secure vehicles.
  53. 53.
    T. Sim, S. Baker, M. Bsat, The CMU pose, illumination, and expression (PIE) database, in Proceedings Fifth IEEE International Conference on Automatic Face and Gesture Recognition (IEEE, New York, 2002), pp. 53–58Google Scholar
  54. 54.
    N. Sushmitha, B. Supriya, R. Prajeeshan, Bio-metric automobile security, International Journal of Scientific Engineering and Technology Research. 4(19), 3550–3554 (2015)Google Scholar
  55. 55.
    G.A. ten Holt, M.J.T. Reinders, E.A. Hendriks, Multi-dimensional dynamic time warping for gesture recognition, in Thirteenth Annual Conference of the Advanced School for Computing and Imaging, vol. 300 (2007)Google Scholar
  56. 56.
    The power to stop drunk driving is now in the palm of your hand.
  57. 57.
    H.C. Tijms, Stochastic Models: An Algorithmic Approach, vol. 303 (Wiley, London, 1994)zbMATHGoogle Scholar
  58. 58.
    M. Turk, A. Pentland, Eigenfaces for recognition. J. Cogn. Neurosci. 3(1), 71–86 (1991)CrossRefGoogle Scholar
  59. 59.
  60. 60.
    L. Yao, C. Lin, J. Deng, F. Deng, J. Miao, K. Yim, G. Wu, Biometrics-based data link layer anonymous authentication in vanets, in 2013 Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS) (IEEE, New York, 2013), pp. 182–187Google Scholar
  61. 61.
    I.J. Faulks,. M. Regan, M. Stevenson, J. Brown, A. Porter, J.D. Irwin (Eds.). Distracted driving. Sydney, NSW: Australasian College of Road Safety, pp. 379–405Google Scholar
  62. 62.
    W. Yuan, Y. Tang, The driver authentication device based on the characteristics of palmprint and palm vein, in 2011 International Conference on Hand-Based Biometrics (ICHB) (IEEE, New York, 2011), pp. 1–5Google Scholar
  63. 63.
    W. Zhao, R. Chellappa, A. Krishnaswamy, Discriminant analysis of principal components for face recognition, in Proceedings of third IEEE International Conference on Automatic Face and Gesture Recognition, 1998 (IEEE, New York, 1998), pp. 336–341Google Scholar
  64. 64.
    Z. Zhu, F. Chen, Fingerprint recognition-based access controlling system for automobiles, in 2011 4th International Congress on Image and Signal Processing (CISP), vol. 4 (IEEE, New York, 2011), pp. 1899–1902CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceCalifornia State UniversityFullertonUSA
  2. 2.Department of Information Systems and Decision SciencesCalifornia State UniversityFullertonUSA

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