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Detecting Driver Drowsiness Using Computer Vision Techniques
Authors: Esra Vural, Müjdat Çetin, Aytül Erçil, Gwen Littlewort, Marian Bartlett, and Javier Movellan
Published in: SIU2008 - IEEE Conference on Signal Processing and Communications Applications
Publication year: 2008
Abstract: Title: Bilgisayarli Goru Yontemleriyle Surucude Uykululugun Sezimi (Detecting Driver Drowsiness Using Computer Vision Techniques)
Abstract:
The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Here we employ machine learning techniques to detect driver drowsiness. The system obtained 98% performance in predicting driver drowsiness. This is the highest prediction rate reported to date for detecting real drowsiness. Moreover, the analysis revealed new information about human behavior during drowsy driving.
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