Drowsy Detection Using Facial Landmarks Extraction and Deep Neural Networks

Introduction

The goal of this article is to explain how you can detect a drowsy person using facial landmarks as an input of a neural network, a 3D convolutional neural network, in this case, to sound an alarm to awake the user and to prevent some kind of accident.

The idea is to extract a group of frames from a webcam and then extract from them the facial landmarks, specifically the position of both eyes, then pass these coordinates to the neural model to get a final classification which will tell us if the user is awake, or falling sleep.

Source de l’article sur DZONE (AI)