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An Embedded Driver Fatigue Detect System Based on Vision

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Advanced Computational Methods in Life System Modeling and Simulation (ICSEE 2017, LSMS 2017)

Abstract

The embedded driver fatigue detect system is a real-time system can detect driver fatigue. In order to improve the performance of embedded driver fatigue monitor system, we propose a new system on chip (SOC) structure for accelerating the fatigue estimate. The new SOC consists two parts including the main processor and support vector machine IP core. An embedded Linux was transplanted and run the main algorithm which consists Haar-Adaboost classifier to locate the face and eyes. The SVM IP core accomplished the task of classifying the eyes’ statues. At last the system will estimate the state with PERCLOS standard. The results show that the system can content the need of real-world.

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Acknowledgements

This work was financially supported by the national natural science foundation of China under Grant (No. 61376028) and (No. 61674100).

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Correspondence to Meihua Xu .

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Shen, H., Xu, M., Ran, F. (2017). An Embedded Driver Fatigue Detect System Based on Vision. In: Fei, M., Ma, S., Li, X., Sun, X., Jia, L., Su, Z. (eds) Advanced Computational Methods in Life System Modeling and Simulation. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 761. Springer, Singapore. https://doi.org/10.1007/978-981-10-6370-1_45

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  • DOI: https://doi.org/10.1007/978-981-10-6370-1_45

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  • Print ISBN: 978-981-10-6369-5

  • Online ISBN: 978-981-10-6370-1

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