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  Published Paper Details:

  Paper Title

DISTRACTION DETECTION BY EYE TRACKING USING RASPBERRY-PI FOR DRIVER SAFETY

  Authors

  SUNITA SHIVAJI SHELKE,  Prof.Sandip Shelke

  Keywords

Moore law, Non-ideal effects, Carbon nanotubes, MOSFET, CNFET, Opamp, 32nm technology

  Abstract


Passively monitoring driver�s eyes can help in detecting state of mind and alertness of driver and thus can reduce risk of accidents. Proposed system includes three main parts 1) Facial feature tracking 2) Eye gaze 3) Eyes off the road and fatigue detection. Video feed from camera installed on car dashboard tracks features of driver in real time (25FPS). Image processing algorithm is developed in OpenCV and implemented on Raspberry Pi board to make a compact embedded system. Different gaze zones are defined, few of which are eyes off the road points. SVM is used to train and classify different combinations of gaze and head pose angles to determine exact point of gaze. Based on algorithm output, if driver�s eyes are off the road or eyes are closed due to fatigue then accordingly audio and steering vibration warnings are given to driver

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2008126

  Paper ID - 197830

  Page Number(s) - 1020-1026

  Pubished in - Volume 8 | Issue 8 | August 2020

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  SUNITA SHIVAJI SHELKE,  Prof.Sandip Shelke,   "DISTRACTION DETECTION BY EYE TRACKING USING RASPBERRY-PI FOR DRIVER SAFETY", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.8, Issue 8, pp.1020-1026, August 2020, Available at :http://www.ijcrt.org/papers/IJCRT2008126.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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