REAL-TIME EYE BLINK DETECTION BASED ON PYTHON
REAL-TIME EYE BLINK DETECTION BASED ON PYTHON
- Author(s): P. Ran 1, 2 and H. Wang 1, 2
- DOI: 10.1049/icp.2021.1312
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- Author(s): P. Ran 1, 2 and H. Wang 1, 2
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View affiliations
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Affiliations:
1:
School of Mechanical and Electrical Engineering, Beijing Information Science and Technology University , Beijing 100192 , China ;
2: Intelligent Robot Technology Institute and Digital Design and Manufacturing Institute , Beijing 100192 , China
Source:
The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020),
2021
p.
98 – 100
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Affiliations:
1:
School of Mechanical and Electrical Engineering, Beijing Information Science and Technology University , Beijing 100192 , China ;
- Conference: The 8th International Symposium on Test Automation & Instrumentation (ISTAI 2020)
- DOI: 10.1049/icp.2021.1312
- ISBN: 978-1-83953-506-2
- Location: Online Conference
- Conference date: 28-29 November 2020
- Format: PDF
With the continuous innovation and development of face recognition and detection technology, it has been widely used in many fields. This paper mainly studies the application of this technology to detect the closed state of drivers' eyes, and according to the detection results give status warning timely, so as to reduce the probability of traffic accidents caused thereby. In this article, Python, OpenCV, Dlib and other third-party libraries are used to obtain the driver's face video through the mobile phone camera and detect the changes of eye aspect ratio (EAR) and mouth aspect ratio (MAR) to determine the driver's state. Finally, it outputs the relationship between EAR and MAR over time for this test.
Inspec keywords: object detection; road accidents; driver information systems; eye; road safety; cameras; face recognition
Subjects: Traffic engineering computing; Computer vision and image processing techniques; Image sensors; Image recognition