Eye Blinking and Drowsiness Detection

Eye Blinking and Drowsiness Detection
Author(s):
Aditi Gaur, Mr. Raghuveer Sachan, Ashutosh Dwivedi, Niharika Singh, Shivansh Pandey, Ankush Singh
Keywords:
dlib library, drowsiness, EAR(Eye Aspect Ratio), Warnings
Abstract
A driver sleepiness detection system is presented, which involves the use of an algorithm to identify driver tiredness. The most relevant visual indications that represent the driver's condition for detecting drowsiness are eye behaviour. An eye aspect ratio and physical landmark data are used in the facial algorithm. The algorithm's landmark detectors are resistant to a wide range of head orientations, face expressions, and illumination conditions. In each video frame, the proposed real-time method will estimate eye aspect ratio, which measures eye open level. It interprets the pattern of eye blinks as EAR values. Potential sleepiness is recognised in this way. Drivers falling asleep due to weariness or long-haul driving, as well as irresponsibility, cause a huge number of road accidents. By delivering non-invasive and simple-to-use specialised gadgets, the suggested system under development can assist prevent this.
Article Details
Unique Paper ID: 152123 Publication Volume & Issue: Volume 8, Issue 2 Page(s): 582 - 586
Article Preview & Download

Share This Article

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org