Tracker for sleepy drivers at the wheel

Abstract

Sleepiness behind the wheel is the major contribution to fatal accidents. Recognizing the drowsiness of the driver is one of the surest methods for measuring driver drowsiness. In this paper a tracker has been created which plans to evaluate driver's fatigue, exhaustion, and diversion throughout driving. The framework composed is a non-intrusive constant checking framework and it consists of camera which keeps a vigilant eye on driver's movements to detect drowsiness. The algorithm developed is unique to any currently published papers, which was a primary objective of the project. The system deals with detecting eyes in an extracted image from video input. All the possible actions have been considered and output is generated accordingly. Drowsiness is determined by observing the eye blinking patterns of the driver. If eyes are found to be closed for a particular time period given by threshold value, the framework reaches the determination that the driver is nodding off and issues a notice flag. The system is implemented using Haar cascade object detector using OpenCV (Open Source Computer Vision Library), which detects eyes from the input image. The system is also able to work under low lighting conditions.