3rd EAI International Conference on Management of Manufacturing Systems

Research Article

Video Post Processing Method For On Board Vehicle Camera with Integrated Eye Tracker

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  • @INPROCEEDINGS{10.4108/eai.6-11-2018.2279712,
        author={Juraj Pancik and Pavel Maxera and Robert Kledus and Michal Belak and Martin Bilek},
        title={Video Post Processing Method For On Board Vehicle Camera with Integrated Eye Tracker},
        proceedings={3rd EAI International Conference on Management of Manufacturing Systems},
        publisher={EAI},
        proceedings_a={MMS},
        year={2018},
        month={12},
        keywords={eye tracker system optical flow driver monitoring systems fatigue detect software},
        doi={10.4108/eai.6-11-2018.2279712}
    }
    
  • Juraj Pancik
    Pavel Maxera
    Robert Kledus
    Michal Belak
    Martin Bilek
    Year: 2018
    Video Post Processing Method For On Board Vehicle Camera with Integrated Eye Tracker
    MMS
    EAI
    DOI: 10.4108/eai.6-11-2018.2279712
Juraj Pancik1,*, Pavel Maxera1, Robert Kledus1, Michal Belak1, Martin Bilek1
  • 1: Institute of Forensic Engineering, Brno University of Technology
*Contact email: juraj.pancik@gmail.com

Abstract

This article describes how to process Eye Tracker System (ETS) data from recorded videos. The research task consisted in confirming the literature fact that the eyes of the moving person (in our case the driver in the car) inadvertently concentrate their position of the eye’s sharp vision center (ESVC) on the place on the scene where the center of the optical flow is located. ETS video records were obtained during experiments in a real vehicle test environment. As part of the post-processing of ETS videos, we determined the numerical difference between the sharp eye viewing position center and the center of the optical flow center (FOE, focus of expansion) for each recorded image. In video post processing, the vibration of the driver’s head in moving car were corrected at it was based on recorded acceleration data. The correcting of acceleration data from the ETS had significantly improved the results of the difference assessment of both centers – ESVC and FOE. A program framework was created in the MATLAB computing environment and it is ready for future use. Lack of concentration in a driver due to fatigue is a major cause of road accidents. This approach (the measurement of distance between ESVC and FOE positions) can be used in role input data generator to develop video processing and artificial intelligence based system to automatically detect driver fatigue and warn the driver, in order to prevent accidents.