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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/15062

Title: Automatic Fatigue Detection of Drivers Through Real Time Eye Tracking
Authors: Tayyaba Azim
M. Arfan Jaffar
Anwar M. Mirza
Keywords: SVM, Yawning detection, Pupil Detection
Issue Date: 2010
Abstract: This paper presents a non-intrusive fatigue detection system based on the video analysis of drivers. The system relies on real time eye tracking to characterize the level of alertness of the driver. The parameters used for detecting fatigue are: eye closure and the duration measured through eye state information. . Initially, the face is located through Viola-Jones face detection method to ensure the presence of driver in video frame. The pupils are also detected in the upper part of the face window on the basis of radii, inter-pupil distance and angle. The monitored information of eyes is further passed to SVM (Support Vector Machines) that classify the true state of the driver. The system has been tested using real data, with different sequences recorded in day and night driving conditions, and with users belonging to different race and gender.
URI: http://hdl.handle.net/123456789/15062
Appears in Collections:College of Computer and Information Sciences

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