Measuring driver cognitive distraction through lips and eyebrows

<span>Cognitive distraction is one of the several contributory factors in road accidents. A number cognitive detection methods have been developed. One most popular based on physiological measurement. Head orientation, gaze rotation, blinking and pupil diameter are among parameters that measured for driver distraction. In this paper, lips eyebrows studied. These new features human facial expression obvious can be easily when a person There types movement captured to indicate Correlation classification techniques used paper performance measurement comparison. Real time driving experiment was setup faceAPI installed car capture driver’s expression. Linear regression, support vector machine (SVM), static Bayesian network (SBN) logistic regression (LR) study. Results showed strongly correlated significant role improving detection. Dynamic (DBN) with different confidence levels also study classify whether distracted or not.</span>