Eye State in Drive Fatigue Detection Based on Sparse Representation

doi:10.7517/j.issn.1674-0475.2016.01.095

Abstract

Abstract:

In this paper, we proposed an eyes state in driver fatigue recognition algorithm based on sparse representation in order to solve the problems that in traditional contact detection, just like affect driver, low recognition rate, etc. First,construct a complete redundant dictionary to training set using K-SVD method and sparse representation the test images employing orthogonal matching pursuit method. Then determine the error between the test images and the reconstructed images. At last,determine the type of test images and judge the state of test images. And contrast the K-SVD to the other dictionary learning methods and sparse representation methods, the experimental results showedthat the K-SVD algorithm combined with OMP obtained better recognition effect.

Key words: driver fatigue, eye state, sparse representation, K-SVD, OMP

WANG Dongmei, FENG Cai, WANG Haipeng, YU Weibo. Eye State in Drive Fatigue Detection Based on Sparse Representation[J]. Imaging Science and Photochemistry, 2016, 34(1): 95-101.

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