Drowsiness Detection in Drivers Using Facial Feature Analysis

Drowsiness Detection in Drivers Using Facial Feature Analysis

Drowsiness has been recognized as a leading factor in road accidents worldwide. Despite considerable research in this area, this paper aims to improve the precision of drowsiness detection specifically for long-haul travel by employing the Dlib-based facial feature detection algorithm. This study pr...

Full description

Saved in:
Bibliographic Details
Main Authors: Ebenezer Essel, Fred Lacy, Fatema Albalooshi, Wael Elmedany, Yasser Ismail
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Applied Sciences
Subjects:
driver fatigue
Eye Closure Ratio
Mouth Aperture Ratio
facial landmark detection
static threshold
adaptive threshold
Online Access:https://www.mdpi.com/2076-3417/15/1/20
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items