A monitoring method of driver mouth behavior based on machine vision

When we use the computer vision to inspect the driver's driving behavior, the identifying of the mouth state is one of the key technologies. In fact, when a driver drives in a normal, talking or dozing state, his/her mouth opening degree will be quite different. According to this fact, this paper uses the Fisher classifier to extract the mouth shape and position, then uses the mouth region's geometry character as the feature value, and put all of these features together to make up an eigenvector as the input of a three-level Bp network, then we get the output among three different spirit states. The experiment results show that this new method can inspect the driver's mouth region state accurately and quickly.