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Mexican International Conference on Artificial Intelligence

MICAI 2017: Advances in Computational Intelligence pp 272–281Cite as

Driver’s Drowsiness Detection Through Computer Vision: A Review

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10633)

Abstract

Drowsiness and sleepiness of driver is an important cause of road accident on expressways, highways, and motorways. These accidents not only results in economic loss but may also in physical injuries, which could result permanent disability or even death. The aim of this research is to minimize this cause of road accidents. Safe driving requirement is unavoidable and to attain this, driver’s drowsiness detection system is to be incorporate in vehicles. Drowsiness detection using vehicle-based, physiological, and behavioral change measurement system is possible with embedded pros and cons. Advancements in the field of image processing and development of faster and cheaper processors direct researches to focus on behavioral change measurement system for drowsiness detection. Computer vision based drowsiness detection is possible by closely monitoring the drowsiness symptoms like eye blinking intervals, yawning, eye closing duration, head position etc. The presented paper deals with merits and demerits of the drowsiness symptoms measurement mechanism and computer vision based drowsiness detection systems. The conclusion of the research is that by designing a hybrid computer vision based drowsy driver detection system dependability achieved. The proposed system is non-intrusive in nature and helpful in attaining safer roads by limiting potential accidental threat due to driver drowsiness.

Keywords

  • Drowsiness detection
  • Computer vision
  • Image processing
  • Eye blinking
  • Yawning
  • PERCLOS

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Author information

Authors and Affiliations

  1. Department of Computer Science, Superior University, Lahore, Pakistan

    Muhammad Rizwan Ullah

  2. Department of Computer Science, University of Engineering and Technology, Lahore, Pakistan

    Muhammad Aslam

  3. Department of Electrical Engineering, COMSATS Institution of Information Technology, Islamabad, Pakistan

    Muhammad Imran Ullah

  4. Department of Computer Science, CINVESTAV, Mexico City, Mexico

    Martinez-Enriquez Ana Maria

Authors
  1. Muhammad Rizwan Ullah
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  2. Muhammad Aslam
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  3. Muhammad Imran Ullah
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  4. Martinez-Enriquez Ana Maria
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Corresponding author

Correspondence to Muhammad Aslam .

Editor information

Editors and Affiliations

  1. Universidad Autónoma del Estado de Hidalgo, Pachuca, Mexico

    Félix Castro

  2. INFOTEC Aguascalientes, Aguascalientes, Mexico

    Sabino Miranda-Jiménez

  3. Tecnológico de Monterrey, Atizapán de Zaragoza, Mexico

    Miguel González-Mendoza

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Ullah, M.R., Aslam, M., Ullah, M.I., Maria, ME.A. (2018). Driver’s Drowsiness Detection Through Computer Vision: A Review. In: Castro, F., Miranda-Jiménez, S., González-Mendoza, M. (eds) Advances in Computational Intelligence. MICAI 2017. Lecture Notes in Computer Science(), vol 10633. Springer, Cham. https://doi.org/10.1007/978-3-030-02840-4_22

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  • DOI: https://doi.org/10.1007/978-3-030-02840-4_22

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