：Aiming at the problem of fatigue driving state recognition in traffic safety, the recognition rate of using a single fatigue driving feature is low. This paper studies and proposes a fatigue recognition method based on the weighted sum of facial multi-features. The eye fatigue parameters, such as continuous eye closing time, eye closing frame ratio and blink frequency, are extracted by human eye state detection algorithm. The number and duration of yawning are obtained through yawning state detection, the nodding frequency is obtained through head motion state analysis, and a driving fatigue state detection model integrating the above six characteristics is established to evaluate the driver’s fatigue level and give the corresponding early warning. The experimental test data are selected from part of the NTHU driver fatigue detection video data set. After experimental adjustment, it is found that this method has high recognition accuracy and provide a good recognition effect.