Work

Driver Drowsiness Warning System Using Visual Information for Both Diurnal and Nocturnal Illumination Conditions

Year: 2010

Type: article

Abstract: Every year, traffic accidents due to human errors cause increasing amounts of deaths and injuries globally. To help reduce the amount of fatalities, in the paper presented here, a new module for Advanced Driver Assistance System (ADAS) which deals with automatic driver drowsiness detection based on visual information and Artificial Intelligence is presented. The aim of this system is to locate, track, and analyze both the drivers face and eyes to compute a drowsiness index, where this real-time system works under varying light conditions (diurnal and nocturnal driving). Examples of different images of drivers taken in a real vehicle are shown to validate the algorithms used.

Source: EURASIP Journal on Advances in Signal Processing

DOI: 10.1155/2010/438205

Authors: MarcoJavier Flores, JoséMaría Armingol, Arturo de la Escalera

Institution: Universidad Carlos III de Madrid

Language: English

Topic: Sleep and Work-Related Fatigue

Subfield: Experimental and Cognitive Psychology

Field: Psychology

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $1,790

OpenAlex ID: W1993192093

FWCI: 4.593

Cites: 36

Cited by: 87

Related to: 10