Computer Science ›› 2015, Vol. 42 ›› Issue (3): 191-194, 200.doi: 10.11896/j.issn.1002-137X.2015.03.039

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Fatigue Recognition Algorithm Based on Deep Learning

ZHOU Hui, ZHOU Liang and DING Qiu-lin   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Current domestic and overseas fatigue recognition algorithms are implemented using fatigue features which are mostly singular and man-made.Most of those algorithms have complex structure,low efficiency and weak adaptability for drivers’ individual behavior habit.To this end,the paper put forward a fatigue recognition algorithm based on deep learning.It introduces deep belief network (DBN) to simulate the data distribution of input images,extracts fatigue features automatically layer by layer,and then recognizes state of fatigue from video images based on time window.The algorithm adjusts the learning rate of the net adaptively to reduce pre-training time,uses feedback mechanism to let the net evolve by itself and as a consequence improves its adaptability for user personalized fatigue features.The experimental result shows that our algorithm acquires good fatigue features,and its misjudgment rate reduces gradually along with incremental time.

Key words: Fatigue recognition,Deep learning,DBN,Fatigue feature,Feedback mechanism

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