Driver Distraction Identification with an Ensemble of Convolutional Neural Networks
Joint Authors
Eraqi, Hesham M.
Abouelnaga, Yehya
Saad, Mohamed H.
Moustafa, Mohamed N.
Source
Journal of Advanced Transportation
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-02-13
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic accidents worldwide and the number has been continuously increasing over the last few years.
Nearly fifth of these accidents are caused by distracted drivers.
Existing work of distracted driver detection is concerned with a small set of distractions (mostly, cell phone usage).
Unreliable ad hoc methods are often used.
In this paper, we present the first publicly available dataset for driver distraction identification with more distraction postures than existing alternatives.
In addition, we propose a reliable deep learning-based solution that achieves a 90% accuracy.
The system consists of a genetically weighted ensemble of convolutional neural networks; we show that a weighted ensemble of classifiers using a genetic algorithm yields a better classification confidence.
We also study the effect of different visual elements in distraction detection by means of face and hand localizations, and skin segmentation.
Finally, we present a thinned version of our ensemble that could achieve 84.64% classification accuracy and operate in a real-time environment.
American Psychological Association (APA)
Eraqi, Hesham M.& Abouelnaga, Yehya& Saad, Mohamed H.& Moustafa, Mohamed N.. 2019. Driver Distraction Identification with an Ensemble of Convolutional Neural Networks. Journal of Advanced Transportation،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1169843
Modern Language Association (MLA)
Eraqi, Hesham M.…[et al.]. Driver Distraction Identification with an Ensemble of Convolutional Neural Networks. Journal of Advanced Transportation No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1169843
American Medical Association (AMA)
Eraqi, Hesham M.& Abouelnaga, Yehya& Saad, Mohamed H.& Moustafa, Mohamed N.. Driver Distraction Identification with an Ensemble of Convolutional Neural Networks. Journal of Advanced Transportation. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1169843
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1169843