DocumentCode
2951426
Title
Detection of the Tiredness Level of Drivers Using Machine Vision Techniques
Author
Jiménez, Robinson ; Prieto, Flavio ; Grisales, Victor H.
Author_Institution
Grupo de Investig. en Autom.-GAUNAL, Univ. Nac. de Colombia, Bogota, Colombia
fYear
2011
fDate
15-18 Nov. 2011
Firstpage
97
Lastpage
102
Abstract
This paper presents a machine vision system to detect fatigue in drivers based on the percentage of closing eyes and detection of yawning and nodding. The system outputs are no fatigue, alarm and critical stage (fatigue). The characteristics are extracted from videos by using image processing techniques such as histogram analysis and color spaces. The decision on the tiredness level is the result of a combination of extracted characteristics. The global performance achieved in characteristic extraction is about 90% and 86% for classification, the processing time to produce a response is close to 40 ms.
Keywords
computer vision; face recognition; fatigue; feature extraction; image classification; psychology; video signal processing; alarm stage; characteristic extraction; closing eyes; color spaces; critical stage; drivers; fatigue detection; histogram analysis; image processing techniques; machine vision technique; nodding detection; tiredness level detection; yawning detection; Apertures; Face; Fatigue; Magnetic heads; Mouth; Videos; Fatigue detection; machine vision; nodding; yawing;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronics, Robotics and Automotive Mechanics Conference (CERMA), 2011 IEEE
Conference_Location
Cuernavaca, Morelos
Print_ISBN
978-1-4577-1879-3
Type
conf
DOI
10.1109/CERMA.2011.23
Filename
6125812
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