Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering

Design and Implementation of Embedded Driver Fatigue Monitor System

Authors
H.M. Shen, M.H. Xu
Corresponding Author
H.M. Shen
Available Online July 2015.
DOI
10.2991/aiie-15.2015.29How to use a DOI?
Keywords
fatigue; embedded; PERCLOS; classifier
Abstract

In order to improve the performance of embedded driver fatigue monitor system, this article designed and implemented a new system based on Soc. Thisdesignadopts the ARM as the core processor which isconnected to other peripheral by FPGA. The system also uses the embedded Linux to run the main algorithm which consists two Haar-Adaboost classifier to locate the eyes and classify the status of eye by support victor machine. At last by using PERCLOS standardthe system will judge whether the driver is fatigue. Experimental results show that the system has a good real-time performanceand the processing rate can reach 25 frames per second.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
Series
Advances in Intelligent Systems Research
Publication Date
July 2015
ISBN
10.2991/aiie-15.2015.29
ISSN
1951-6851
DOI
10.2991/aiie-15.2015.29How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - H.M. Shen
AU  - M.H. Xu
PY  - 2015/07
DA  - 2015/07
TI  - Design and Implementation of Embedded Driver Fatigue Monitor System
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 103
EP  - 106
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.29
DO  - 10.2991/aiie-15.2015.29
ID  - Shen2015/07
ER  -