Research on Driver’s Distracted Behavior Detection Method Based on Multiclass Classification and SVM

Abstract

To reduce the occurrence of traffic accidents caused by distraction. a detection method based on histogram of oriented gradient (HOG) and support vector machine (SVM) is proposed for driver’s distraction behavior in this paper. Interest region of driver was detected first from video image, also the image was enhanced, denoised and normalized. Then the histogram of oriented gradient is used to extract the feature of the image. Meanwhile, the cross-validation method is used to optimize parameters in SVM. Finally, the effectiveness of the method is verified by compared with classical SVM algorithm and Local Binary Pattern algorithm (LBP) based on SVM algorithms. The results show that, the proposed method can obtain better classification accuracy.