About: CLASSIFICATION OF DRIVER'S DROWSINESS FROM STEERING WHEEL MOTION UNDER REAL TRAFFIC CONDITIONS     Goto   Sponge   NotDistinct   Permalink

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Description
  • To develop a system for drivers drowsiness recognition is a challenging task in the modern car transportation. Many studies have promising results. Unfortunately most data is acquired in the laboratory conditions. Therefore proving drowsiness detection reliability and accuracy in real traffic is difficult. The analyzed data in this paper is acquired from the real traffic and hence it contains all uncertainty. An in-direct measurement from the vehicle CAN bus has been chosen for data acquisition in order to not affect the driver. The data is preprocessed according to the assumptions about drivers behavior and transformed to the frequency domain by means of the orthogonal transform (STFT, CWT and DWT). Subsequently, in the frequency domain, more than 70 000 features are generated. By means of the filter feature selection, 10 best features are chosen for a prediction. Finally, 1-NN model is used for prediction accuracy estimation.
  • To develop a system for drivers drowsiness recognition is a challenging task in the modern car transportation. Many studies have promising results. Unfortunately most data is acquired in the laboratory conditions. Therefore proving drowsiness detection reliability and accuracy in real traffic is difficult. The analyzed data in this paper is acquired from the real traffic and hence it contains all uncertainty. An in-direct measurement from the vehicle CAN bus has been chosen for data acquisition in order to not affect the driver. The data is preprocessed according to the assumptions about drivers behavior and transformed to the frequency domain by means of the orthogonal transform (STFT, CWT and DWT). Subsequently, in the frequency domain, more than 70 000 features are generated. By means of the filter feature selection, 10 best features are chosen for a prediction. Finally, 1-NN model is used for prediction accuracy estimation. (en)
Title
  • CLASSIFICATION OF DRIVER'S DROWSINESS FROM STEERING WHEEL MOTION UNDER REAL TRAFFIC CONDITIONS
  • CLASSIFICATION OF DRIVER'S DROWSINESS FROM STEERING WHEEL MOTION UNDER REAL TRAFFIC CONDITIONS (en)
skos:prefLabel
  • CLASSIFICATION OF DRIVER'S DROWSINESS FROM STEERING WHEEL MOTION UNDER REAL TRAFFIC CONDITIONS
  • CLASSIFICATION OF DRIVER'S DROWSINESS FROM STEERING WHEEL MOTION UNDER REAL TRAFFIC CONDITIONS (en)
skos:notation
  • RIV/00216305:26220/12:PU99587!RIV14-GA0-26220___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/09/1897)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 127367
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/12:PU99587
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • drowsiness, driver, Wavelet transform, Fourier transform, feature generation, AUC, LOOCV, CV (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [A5D04123E186]
http://linked.open...v/mistoKonaniAkce
  • Brno University of Technology
http://linked.open...i/riv/mistoVydani
  • Neuveden
http://linked.open...i/riv/nazevZdroje
  • MENDEL 2012, 18th International Conference on Soft Computing
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Kučera, Pavel
  • Honzík, Petr
  • Haupt, Daniel
  • Hynčica, Ondřej
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Neuveden
https://schema.org/isbn
  • 978-80-214-4540-6
http://localhost/t...ganizacniJednotka
  • 26220
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