关键词: 随机森林, 人脸轮廓点, 车辆操控活跃度, 疲劳驾驶

Abstract:

Complex traffic environment, personal and social factors restrict the application effect of fatigue driving recognition technology. This paper presents a fatigue driving recognition algorithm based on the fusion analysis of driver’s face state in video and vehicle driving state data. The algorithm calculates the aspect ratio of eyes and mouth based on the extracted face contour points using Dlib database, and then generates the orbital and yawn features. At the same time, the vehicle manipulation activity features based on the linear fitting trend extraction method are obtained. The improved random forest model is used to identify the fatigue state. The model evaluates the importance of features based on weight, improves the validity of tree nodes splitting, and gives the method of regulating the number of trees in forest. The experimental results show that the average accuracy of fatigue driving recognition of the proposed algorithm reaches 92.06%, and it has good computational efficiency meanwhile, which verifies its effectiveness.

Key words: random forest, face contour points, vehicle manipulation activity, fatigue driving