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DriverAssit is a project for evaluating driver drowsiness and distracted and impaired driving on the road during my PhD. 

It's a two-monocular-cameras-based system consisting of Lane detection and tracking system, Face detection and tracking system, and Fusion center based on evidence theory. 

The project is developed for the object of scientific research. If interested, please allude to my contributions (dblp indexed):

[1] Xuanpeng Li, Emmanuel Seignez, Pierre Loonis: Vision-based estimation of driver drowsiness with ORD model using evidence theory. Intelligent Vehicles Symposium 2013: 666-671   
[2] Xuanpeng Li, Emmanuel Seignez, Pierre Loonis: Reliability-based driver drowsiness detection using Dempster-Shafer theory. ICARCV 2012: 1059-1064

The project is in progress. Our aim is to provide a comprehensive evaluation system of vehicle safety in 2015.   

License
DriverAssist is under GPL2 license and using OpenCV under a BSD license. It is only for a non-commercial purpose or private study. 

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