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International Multi-Conference on Advanced Computer Systems

ACS 2018: Advances in Soft and Hard Computing pp 396–407Cite as

Driver Drowsiness Estimation by Means of Face Depth Map Analysis

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 889))

Abstract

In the paper a problem of analysing facial images captured by depth sensor is addressed. We focus on evaluating mouth state in order to estimate the drowsiness of the observed person. In order to perform the experiments we collected visual data using standard RGB-D sensor. The imaging environment mimicked the conditions characteristic for driver’s place of work. During the investigations we trained and applied several contemporary general-purpose object detectors known to be accurate when working in visible and thermal spectra, based on Haar-like features, Histogram of Oriented Gradients, and Local Binary Patterns. Having face detected, we apply a heuristic-based approach to evaluate the mouth state and then estimate the drowsiness level. Unlike traditional, visible light-based methods, by using depth map we are able to perform such analysis in the low level of even in the absence of cabin illumination. The experiments performed on video sequences taken in simulated conditions support the final conclusions.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Żołnierska Str. 52, 71–210, Szczecin, Poland

    Paweł Forczmański & Kacper Kutelski

Authors
  1. Paweł Forczmański
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  2. Kacper Kutelski
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Corresponding author

Correspondence to Paweł Forczmański .

Editor information

Editors and Affiliations

  1. West Pomeranian University of Technology in Szczecin, Szczecin, Poland

    Jerzy Pejaś

  2. West Pomeranian University of Technology in Szczecin , Szczecin, Poland

    Imed El Fray

  3. West Pomeranian University of Technology in Szczecin, Szczecin, Poland

    Tomasz Hyla

  4. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

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Forczmański, P., Kutelski, K. (2019). Driver Drowsiness Estimation by Means of Face Depth Map Analysis. In: Pejaś, J., El Fray, I., Hyla, T., Kacprzyk, J. (eds) Advances in Soft and Hard Computing. ACS 2018. Advances in Intelligent Systems and Computing, vol 889. Springer, Cham. https://doi.org/10.1007/978-3-030-03314-9_34

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