Driver Drowsiness Detection using Facial Recognition
Eagalaivan R, Saravanan S, Gokul Krishna, Mrinal mahindran
Every year road accidents are increasing and people are losing lives. The root cause of many accidents is due to fatigue of drivers . There are some ongoing research happening to identify the fatigueness of driver many methods have been identified and systems are prepared the use of such systems are expensive and hence it is difficult to implement in every vehicles.Therefore, in this paper, a light-weight, real time driver’s drowsiness detection system is developed and implemented on Android application and as a python application for remote server functioning . The system captures the video frames and detects the driver's face in every frame by employing image processing techniques. The system is capable of detecting facial landmarks, computes Eye Aspect Ratio (EAR) and Eye Closure Ratio (ECR) to detect driver’s drowsiness based on thresholding, thresholding is modified based on driver distance towards the camera. Machine learning algorithms have been employed to test the efficacy of the suggested system. Empirical results demonstrate that the suggested model is able to achieve accuracy of 84% using random forest classifiers.
Article Details
Unique Paper ID: 150832

Publication Volume & Issue: Volume 7, Issue 10

Page(s): 224 - 229
Article Preview & Download

Share This Article

Conference Alert


International conference on Management, Science, Technology, Engineering, Pharmact and Humanities.

Go To Issue

Call For Paper

Volume 8 Issue 4

Last Date 25 September 2021

About Us enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on

Social Media

Google Verified Reviews

Contact Details