Intelligent Transportation Systems: Driver Fatigue Monitoring

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

Detection and Classification of Vehicles

Overview

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.

Publications:

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.

Demos:

Driver fatigue monitoring Movie 1(2.0M)

Driver fatigue monitoring Movie 2 (2.5M)

People:

Faculty Nikolaos Papanikolopoulos	Research Associate Osama Masoud
Graduate Students Stefan Atev Nathaniel Bird