文献类型： 外文期刊

作者： Fan, Xiao ¹ ; Sun, Yanfeng ¹ ; Yin, Baocai ¹ ; Guo, Xiuming ³ ;

作者机构： 1.Beijing Univ Technol, Beijing Key Lab Multimedia & Intelligent Software, Coll Comp Sci & Technol, Beijing 100124, Peoples R China

2.Cogent Beijing R&D Ctr, Beijing 100089, Peoples R China

3.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

关键词： Human fatigue; Multi-scale; Dynamic feature; Feature fusion; AdaBoost algorithm

期刊名称：PATTERN RECOGNITION LETTERS （ 影响因子：3.756； 五年影响因子：3.615 ）

ISSN： 0167-8655

年卷期： 2010 年 31 卷 3 期

页码：

收录情况： SCI

摘要： 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. (C) 2009 Elsevier B.V. All rights reserved.