An eye fatigue recognition system using YOLOv2
Document Type
Conference Item
Publication Date
1-1-2021
Abstract
The rapid increase in global population significantly drives the hiking demand for transportations. This trend further leads to the increase in the number of road traffic accidents globally. Based on a study, fatigue due to prolonged driving is one of the leading causes for traffic accidents. With a customized Graphical User Interface (GUI), this work aims to develop an eye fatigue recognition system using YOLOv2 model. The proposed method used PERCLOS and blink rate parameters as indicators to determine the alertness of the user. This proposed method achieved a real-time average accuracy of 99.23 in normal lighting conditions and 98.57 in low light conditions. © 2021 IEEE.
Keywords
Highway accidents, Blink rates, Driving alertness, Eye fatigue, Eye fatigue recognition, Global population, PERCLOS, Rate parameters, Recognition systems, Road traffic accidents, YOLOv2, Graphical user interfaces
Divisions
sch_ecs
Funders
None
Publication Title
3rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies, i-PACT 2021
Event Title
rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies, i-PACT 2021
Event Location
Virtual, Online
Event Dates
27 November 2021
Event Type
conference