Driver Fatigue Features Extraction

Driver fatigue is the main cause of traffic accidents. How to extract the effective features of fatigue is important for recognition accuracy and traffic safety. To solve the problem, this paper proposes a new method of driver fatigue features extraction based on the facial image sequence. In this m...

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Bibliographic Details
Main Authors: Gengtian Niu, Changming Wang
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2014/860517
Description
Summary:Driver fatigue is the main cause of traffic accidents. How to extract the effective features of fatigue is important for recognition accuracy and traffic safety. To solve the problem, this paper proposes a new method of driver fatigue features extraction based on the facial image sequence. In this method, first, each facial image in the sequence is divided into nonoverlapping blocks of the same size, and Gabor wavelets are employed to extract multiscale and multiorientation features. Then the mean value and standard deviation of each block’s features are calculated, respectively. Considering the facial performance of human fatigue is a dynamic process that developed over time, each block’s features are analyzed in the sequence. Finally, Adaboost algorithm is applied to select the most discriminating fatigue features. The proposed method was tested on a self-built database which includes a wide range of human subjects of different genders, poses, and illuminations in real-life fatigue conditions. Experimental results show the effectiveness of the proposed method.
ISSN:1024-123X
1563-5147