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作者:

Xiao, Fan (Xiao, Fan.) | Yanfeng, Sun (Yanfeng, Sun.) (学者:孙艳丰) | Baocai, Yin (Baocai, Yin.) (学者:尹宝才)

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EI Scopus

摘要:

Driver fatigue is a significant reason for many traffic accidents. We propose a novel multi-scale dynamic feature with feature level fusion for driver fatigue detection from facial image sequences. First, Gabor filters are employed to extract multi-scale and multi-orientation features from each image. Features of the same scale are then fused according to a fusion rule to produce a single feature. 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 concatenated as dynamic features. Finally AdaBoost algorithm is applied to extract the most discriminative features and construct a strong classifier for fatigue detection. The test data contains 600 image sequences from thirty people. Experimental results show the validity of the proposed approach, and the average correct rate is 99.33% which is much better than the baselines. © 2008 IE.

关键词:

Adaptive boosting Feature extraction Gabor filters Gesture recognition

作者机构:

  • [ 1 ] [Xiao, Fan]Beijing Key Laboratory of Multimedia and Intelligent Software, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Yanfeng, Sun]Beijing Key Laboratory of Multimedia and Intelligent Software, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Baocai, Yin]Beijing Key Laboratory of Multimedia and Intelligent Software, College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China

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年份: 2008

语种: 英文

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WoS核心集被引频次: 0

SCOPUS被引频次: 2

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