Driver drowsiness recognition based on computer vision technology
Year: 2012
Type: article
Abstract: Driver drowsiness is one of the major causes of traffic accidents. This paper presents a nonintrusive drowsiness recognition method using eye-tracking and image processing. A robust eye detection algorithm is introduced to address the problems caused by changes in illumination and driver posture. Six measures are calculated with percentage of eyelid closure, maximum closure duration, blink frequency, average opening level of the eyes, opening velocity of the eyes, and closing velocity of the eyes. These measures are combined using Fisher's linear discriminant functions using a stepwise method to reduce the correlations and extract an independent index. Results with six participants in driving simulator experiments demonstrate the feasibility of this video-based drowsiness recognition method that provided 86% accuracy.
Source: Tsinghua Science & Technology
Authors: Wei Zhang, Bo Cheng, Yingzi Lin
Institutions: Tsinghua University, Northeastern University
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W1484788869