In order to detect the driver’s fatigue driving situation in time, this paper proposed a yawn detection method based on Dlib and variant Transformer. First, the yawn feature matrix of the driver’s eyes and mouth was constructed based on the face key point model of Dlib. Then a variant Transformer model was proposed in the field of video detection, to extract the yawn feature matrix and classify the results. Finally, it was verified based on the YawDD dataset. The results show that the yawn detection accuracy of the proposed algorithm is 96.8%, which is higher than the existing algorithms, and is suitable for the detection of yawning behavior when the driver is fatigued.

Yawn detection  /  Dlib  /  Yawning features matrix  /  Variant Transformer  /  YawDD