Automatic Fatigue Detection System

نویسنده

  • T. Tinoco De Rubira
چکیده

Fatigue is the cause of a large number of car accidents in the United States. Studies done by the National Highway Traffic Safety Administration, estimate that about 1,550 deaths, 71,000 injuries, and 12.5 billion dollars in monetary losses are the cost of fatigue related car accidents each year. To prevent these accidents, there are a number of devices available in the market. Many of these products are small devices worn by drivers on their ear that generate an alarm when the driver’s head falls forward. However, these devices produce the alarm after the driver is no longer in conditions to be driving. The alarm essentially makes the driver wake up and can itself be the cause of an abrupt reaction that can lead to an accident. An alternative and better approach is proposed by [1]. Here, a computer vision-based system is described that keeps track of the eyes and detects the sleep onset of fatigued drivers. The proposed system uses template matching for detecting the state of the eyes. This approach however, is computationally intensive, it is subject-dependent and requires calibration routines for adjusting for light conditions. In this paper, we present a more robust alternative based on machine learning for detecting and tracking the fatigue level of a driver.

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تاریخ انتشار 2009