Abstract
With increase in technology fatigue detection systems with more accuracy are overcoming their previous versions. The main focus of these systems is on robustness, accuracy and cost. Based on these factors this study presents a driver fatigue detection system design. This design uses facial features (eyes and mouth) to determine driver’s vigilance. A hybrid of two commonly known techniques Viola Jones and skin color detection is used as detection technique. Lastly some experimental results are given showing the accuracy and robustness of the proposed system.
Highlights
Driving with drowsiness is one of the major reasons causing traffic accidents
The National Highway Traffic Safety Administration (NHTSA) estimates that 100000 police-reported crashes are directly caused by driver fatigue each year, which result in an estimated 1550 deaths, 71000 injuries (NHTSA)
Eyes and mouth detection: In second step the detected face area is extracted from input image for further processing
Summary
Driving with drowsiness is one of the major reasons causing traffic accidents. The National Highway Traffic Safety Administration (NHTSA) estimates that 100000 police-reported crashes are directly caused by driver fatigue each year, which result in an estimated 1550 deaths, 71000 injuries (NHTSA). This problem has increased the need of developing active safety systems inside vehicle that monitor driver’s level of vigilance and alert drivers after detecting their drowsiness. Fatigue detection from facial expression: Visual behaviors that reflect driver’s level of drowsiness include slow eyelid movement, smaller degree of eye openness, sluggish in facial expression, yawning, sagging posture and frequent nodding.
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Published Version
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