Abstract
Aiming at the problem that the existing fatigue driving detection methods cannot make full use of eye features and semantic information, a driver eye fatigue detection method based on parallel neural network is proposed. This method detects human faces through a multi-task cascaded convolutional network, determines the driver’s eye area according to the face ratio relationship, uses the parallel structure of the convolutional neural network and the residual network to recognize the eye state opening and closing, and according to PERCLOS the criterion is to judge the fatigue state. The experimental results show that the method has a high accuracy rate and can effectively detect the fatigue driving state.
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