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《Transducer and Microsystem Technologies》 2019-05
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Train driver's eyes state detection based on improved ASM algorithm

WANG Shuai;ZHAO Luyang;HE Wei;LI Fengrong;Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Sciences;University of Chinese Academy of Sciences;  
To solve the problem of train driver's fatigue state detection,an improved active shape model( ASM)algorithm is proposed and a fatigue judgment mechanism based on support vector machine( SVM) is designed,realizing the effective detection of the eyes state of train driver during driving. The improved ASM algorithm extracts the local eigenvectors through the multi-scale local binary pattern( MB-LBP),improving the robustness in complex light environment. Considering the effect of the time parameters for the judgment of the fatigue state of the driver,the judgment mechanism use two-level SVM structure. As the result shows,the improved ASM algorithm effectively improves the accuracy of the key point location of face,and the judgment mechanism designed in this article achieves 80 % accuracy in the real dataset testing.
【Fund】: 上海市青年科技英才扬帆计划资助项目(No.15YF1414500);; 中国科学院科技服务网络计划资助项目(KFJ-STS-ZDTP-017)
【CateGory Index】: TP391.41;TP181;U268.48
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