The advancement of computing technology over the
years has provided assistance to drivers mainly in the form of
intelligent vehicle systems. Driver fatigue is a significant factor in
a large number of vehicle accidents. Thus, driver drowsiness
detection has been considered a major potential area so as to
prevent a huge number of sleep induced road accidents. This
paper proposes a vision based intelligent algorithm to detect
driver drowsiness. Previous approaches are generally based on
blink rate, eye closure, yawning, eye brow shape and other hand
engineered facial features. The proposed algorithm makes use of
features learnt using convolutional neural network so as to
explicitly capture various latent facial features and the complex
non-linear feature interactions. A softmax layer is used to classify
the driver as drowsy or non-drowsy. This system is hence used
for warning the driver of drowsiness or in attention to prevent
traffic accidents.We present both qualitative and quantitative
results to substantiate the claims made in the paper.