Intelligent Transportation Systems: Driver Fatigue Monitoring

Artificial Intelligence, Robotics, and Vision Lab
University of Minnesota, Minneapolis, Minnesota

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The driver fatigue project has built a system that tracks the eyes of the driver in order to detect fatigue. It uses a video camera that points directly towards the driver's face. It monitors the driver's eyes in order to detect micro-sleeps (short periods of sleep of about 3-4 seconds). The input to the system is a continuous sequence of images fed from a video camera. From this sequence, the system can analyze the eyes in each image, as well as compare the eyes between frames. The system deals with skin-color information in order to search for the face in the input space. Extensive experiments indicate that the developed system can monitor driver fatigue very effectively in real-world scenarios.


Driver Activity Monitoring through Supervised and Unsupervised Learning. (PDF)
H. Veeraraghavan, S. Atev, N. Bird, P. Schrater and N. Papanikolopoulos. Driver Activity Monitoring through Supervised and Unsupervised Learning. In Proc. IEEE Conf. Intell. Transport. Syst. (ITSC 2005), pp. 895−900, Sep. 2005.
Vision based methods for driver monitoring. (PDF)
E. Wahlstrom, O. Masoud, N.P. Papanikolopoulos. Vision-based methods for driver monitoring. In Proc. IEEE 6th International Conference on Intelligent Transportation Systems, pp. 903-908, Shanghai, China, Oct. 2003.


    Driver fatigue monitoring Movie 1(2.0M)

Driver fatigue monitoring Movie 2 (2.5M)


Nikolaos Papanikolopoulos

Research Associate
Osama Masoud
Graduate Students
Stefan Atev
Nathaniel Bird

This work is supported by grants from the National Science Foundation, Minnesota Department of Transportation, and the Intelligent Transportation Systems Institute.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.