Gabor-based dynamic representation for human fatigue monitoring in facial image sequences

Authors:
Xiao Fan;Yanfeng Sun;Baocai Yin;Xiuming Guo
Affiliations:
Beijing Key Laboratory of Multimedia and Intelligent Software, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China and Cogent Beijing R&D Center, Be ...;Beijing Key Laboratory of Multimedia and Intelligent Software, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China;Beijing Key Laboratory of Multimedia and Intelligent Software, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China;National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
Venue:
Pattern Recognition Letters
Year:
2010

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Abstract

Human fatigue is an important reason for many traffic accidents. To improve traffic safety, this paper proposes a novel Gabor-based dynamic representation for dynamics in facial image sequences to monitor human fatigue. Considering the multi-scale character of different facial behaviors, Gabor wavelets are employed to extract multi-scale and multi-orientation features for each image. Then features of the same scale are fused into a single feature according to two fusion rules to extract the local orientation information. To account for the temporal aspect of human fatigue, the fused image sequence is divided into dynamic units, and a histogram of each dynamic unit is computed and combined as dynamic features. Finally, AdaBoost algorithm is exploited to select the most discriminative features and construct a strong classifier to monitor fatigue. The proposed method was tested on a wide range of human subjects of different genders, poses and illuminations under real-life fatigue conditions. Experimental results show the validity of the proposed method, and an encouraging average correct rate is achieved.