Research Article Open Access
This paper describes a real time system for analyzing video sequences of a driver and determining his/her level of attention. The proposed system deals with the computation of Percent of Eyelid Closure (PERCLOS) as an indicator to detect drowsiness. Driver’s fatigue and drowsiness are the major causes of traffic accidents on road. Monitoring the driver’s vigilance level, and issuing an alert when he/she is not paying enough attention to the road is a promising way to reduce the accidents caused by driver factors. Visual information is acquired using a specially designed solution combining a CCD video camera with an IR illumination system. The system is fully automatic and detects eye position, eye closure and recovers the gaze of the eyes. Experimental results using real images demonstrate the accuracy and robustness of the proposed solution. Thus it could become an important part in the development of the advanced safety vehicle. The driver’s facial information, especially the eye status is often believed to give some clues of his/her drowsiness level. In developing those driver monitoring systems, a reliable real-time driver eye detection method is one of the essential parts. This paper describes a real-time dedicated system for detecting driver-fatigue and drowsiness. This method break traditional way of drowsiness detection to make it real time, it utilizes face detection and eye detection to initialize the location of driver’s eyes; after that an object tracking method is used to keep track of the eyes; finally, we can identify drowsiness state of driver with PERCLOS by identified eye state.
To read the full article Peer-reviewed Article PDF
| Peer-reviewed Full Article
Author(s): K.Subhashini Spurjeon , Yogesh Bahindwar
Driver vigilance, eyelid movement, face position, percent eye closure (PERCLOS), visual fatigue behaviors, Aerospace Engineering,Applied Electronics,Applied Sciences,Biochemistry,Fluid Dynamics,Chromatography Techniques.