Biometrical driver face verification

  • Jolanta Chmielińska Military University of Technology in Warsaw
  • Jacek Jakubowski Military University of Technology in Warsaw
Keywords: road safety, monitoring system, convolutional neural networks, identity verification, face images, driver fatigue, tachogram

Abstract

The paper discusses the problem of face verification in a driver monitoring system for the purpose of traffic safety. Two different methods of face verification were proposed. Both of them are based on a convolutional neural network and were developed with the use of a transfer learning technique. In the paper, the results produced by both proposed method have been presented and compared. Moreover, their advantages and disadvantages have been discussed.

References

Bengio Y., Courville A., Goodfellow I., Deep Learning. Systemy uczące się, Wyd. PWN, Warszawa 2018.
Chmielińska J., Jakubowski J., Zastosowanie sieci konwolucyjnej do wykrywania wybranych symptomów zmęczenia kierowcy, Przegląd Elektrotechniczny, vol. 93, no. 10, 2017, ss. 6-10.
Glorot X., Bordes A., Bengio Y., Deep Sparse Rectifer Neural Networks, Proceedings of the 14th International Conference on Artifcial Intelligence and Statistics (AISTATS), ss. 315-323, 2011.
http://motoryzacja.interia.pl/raporty/raport-polskie-drogi/wiadomosci/news-pomyslowy-sposob-na-oszukanie-tachografu,nId,2366900 (dostępny kwiecień 2018)
https://www.tvn24.pl/wiadomosci-z-kraju,3/tachograf-oszukac-bardzo-latwo-zmuszaja-do-tego-pracodawcy,262569.html (dostępny kwiecień 2018)
Krizhevsky A., Sutskever I., Hinton G. E., Imagenet classification with deep convolutional neural networks, Neural Information Processing Systems Conference (NIPS), 2012.
Krueger G. P., Sustained Work, Fatigue, Sleep Loss and Performance: A Review of the Issues, Work and Stress, An International Journal of Work, Health and Organisations, Volume 3, 1989 - Issue 2.
Rozporządzenie Parlamentu Europejskiego i Rady (UE) Nr 165/2014 z dnia 4 lutego 2014r w sprawie tachografów stosowanych w transporcie drogowym.
Steele F. J., Improved digital tachograph system, patent Nr WO 2006008527 A2, 2006.
Stocerz M., wypowiedź w artykule pt. Kontrole kierowców zawodowych bez zatrzymywania pojazdów, Specjalistyczny Kwartalnik Informacyjny „Czas na transport”, Nr 1 (12), 2018, ss. 68-89.
Taigman Y., Yang M., Ranzato M. A., Wolf L., DeepFace: Closing the Gap to Human-Level Performance in Face Verification, 2014 IEEE Conference on Computer Vision and Pattern Recognition, materiały konferencyjne, ss. 1701-1708.
Thiffault P., Bergeron J., Monotony of road environment and driver fatigue: a simulator study, Accident Analysis and Prevention 35 (2003), ss. 381–391.
Published
2018-09-07
Section
Articles