A CNN-Based Driver’s Drowsiness and Distraction Detection System

Jonathan Flores-Monroy, Mariko Nakano-Miyatake, Hector Perez-Meana, Enrique Escamilla-Hernandez, Gabriel Sanchez-Perez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The driver’s drowsiness and distraction are the principal causes of traffic accidents in the world. To attack this problem, in this paper we propose a visual-based driver’s drowsiness and distraction detection system, which is based on a face detection algorithm and a CNN-based driver state classification. To be useful the proposed system, we consider that the system must be implemented in a compact mobile device with limited memory space and computational power. The proposed system in compact mobile device can be used in any type of vehicle, avoiding accident caused by lack of driver’s alert. The proposed system is evaluated using public dataset, obtaining 95.77% of global accuracy. The proposed system is compared with five finetuned off-the-shelf CNNs, in which the proposed system shows a favorable performance, providing higher operation speed and lower memory requirement compared with these five CNNs, although the detection accuracy is slightly lower compared with the best CNN. The performance of the proposed system guarantees the real-time operation in the compact mobile device.

Original languageEnglish
Title of host publicationPattern Recognition - 14th Mexican Conference, MCPR 2022, Proceedings
EditorsOsslan Osiris Vergara-Villegas, Vianey Guadalupe Cruz-Sánchez, Juan Humberto Sossa-Azuela, Jesús Ariel Carrasco-Ochoa, José Francisco Martínez-Trinidad, José Arturo Olvera-López
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages11
ISBN (Print)9783031077494
StatePublished - 2022
Event14th Mexican Conference on Pattern Recognition, MCPR 2022 - Ciudad Juárez, Mexico
Duration: 22 Jun 202225 Jun 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13264 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th Mexican Conference on Pattern Recognition, MCPR 2022
CityCiudad Juárez


  • Convolutional Neural Networks (CNN)
  • Driver’s distraction detection
  • Driver’s drowsiness detection
  • Finetuning model
  • Real-time implementation


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