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Driver Fatigue Detection Based Intelligent Vehicle Control

Authors: Zutao Zhang; Jiashu Zhang;

Driver Fatigue Detection Based Intelligent Vehicle Control

Abstract

Driver fatigue problem is one of the important factors that cause traffic accidents. Therefore the vision-based driver fatigue detection is the most prospective commercial applications of HCI. However, it is a challenging issue due to a variety of factors such as head and eyes moving fast, external illuminations interference and realistic lighting conditions, etc. This tends to significantly limit its scope of application. In this paper, we present an intelligent vehicle control based on driver fatigue detection. Firstly, the face is located using Haar algorithm and eye location is found with projection technique. After finding eye templates, we propose a new real time eye tracking method based on Unscented Kalman Filter. Thirdly, driver fatigue can be detected whether the eyes are closed over 5 consecutive frames using vertical projection matching. Finally, if driver fatigue is confirmed, the vehicle Cruise Control is start-up with slow speed, and maintains set slow speed such as 5 km/h. The experimental results show that intelligent vehicle control based on driver fatigue detection will be availability in traffic.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
28
Top 10%
Top 10%
Top 10%
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