Smart Real-Time Video Surveillance Platform for Drowsiness Detection Based on Eyelid Closure
Joint Authors
Kwak, Kyungsup
Ullah, Farman
Tayab Khan, Muhammad
Anwar, Hafeez
Ur Rehman, Ata
Ullah, Rehmat
Iqbal, Asif
Lee, Bok-Hee
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-19
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
We propose drowsiness detection in real-time surveillance videos by determining if a person’s eyes are open or closed.
As a first step, the face of the subject is detected in the image.
In the detected face, the eyes are localized and filtered with an extended Sobel operator to detect the curvature of the eyelids.
Once the curves are detected, concavity is used to tell whether the eyelids are closed or open.
Consequently, a concave upward curve means the eyelid is closed whereas a concave downwards curve means the eye is open.
The proposed method is also implemented on hardware in order to be used in real-time scenarios, such as driver drowsiness detection.
The evaluation of the proposed method used three image datasets, where images in the first dataset have a uniform background.
The proposed method achieved classification accuracy of up to 95% on this dataset.
Another benchmark dataset used has significant variations based on face deformations.
With this dataset, our method achieved classification accuracy of 70%.
A real-time video dataset of people driving the car was also used, where the proposed method achieved 95% accuracy, thus showing its feasibility for use in real-time scenarios.
American Psychological Association (APA)
Tayab Khan, Muhammad& Anwar, Hafeez& Ullah, Farman& Ur Rehman, Ata& Ullah, Rehmat& Iqbal, Asif…[et al.]. 2019. Smart Real-Time Video Surveillance Platform for Drowsiness Detection Based on Eyelid Closure. Wireless Communications and Mobile Computing،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1212019
Modern Language Association (MLA)
Tayab Khan, Muhammad…[et al.]. Smart Real-Time Video Surveillance Platform for Drowsiness Detection Based on Eyelid Closure. Wireless Communications and Mobile Computing No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1212019
American Medical Association (AMA)
Tayab Khan, Muhammad& Anwar, Hafeez& Ullah, Farman& Ur Rehman, Ata& Ullah, Rehmat& Iqbal, Asif…[et al.]. Smart Real-Time Video Surveillance Platform for Drowsiness Detection Based on Eyelid Closure. Wireless Communications and Mobile Computing. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1212019
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1212019