Design of multi-feature fusion driver fatigue state detection system based on FPGA

QU Shi-ru; PENG Ji-chang

doi:10.13873/j.1000-97872013.05.029

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Design of multi-feature fusion driver fatigue state detection system based on FPGA

更新时间：2025-09-11

- Design of multi-feature fusion driver fatigue state detection system based on FPGA
- Vol. 32, Issue 5, Pages: 86-88+91(2013)
- 作者机构：
  
  西北工业大学自动化学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872013.05.029
  CLC： TP274;TP391.41
- Published：2013
- 稿件说明：
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[1]曲仕茹,彭纪昌.基于FPGA的多特征融合司机疲劳状态检测系统设计[J].传感器与微系统,2013,32(05):86-88+91.

QU Shi-ru, PENG Ji-chang. Design of multi-feature fusion driver fatigue state detection system based on FPGA[J]. 2013, 32(5): 86-88+91.
[1]曲仕茹,彭纪昌.基于FPGA的多特征融合司机疲劳状态检测系统设计[J].传感器与微系统,2013,32(05):86-88+91. DOI： 10.13873/j.1000-97872013.05.029.

QU Shi-ru, PENG Ji-chang. Design of multi-feature fusion driver fatigue state detection system based on FPGA[J]. 2013, 32(5): 86-88+91. DOI： 10.13873/j.1000-97872013.05.029.

摘要

驾驶员的疲劳驾驶是造成交通事故的重要因素

为了实时有效地检测驾驶员的驾驶状态

设计了一种融合多种疲劳特征进行疲劳状态判定的检测算法

并构建了车载的基于现场可编程门阵列（FPGA）的嵌入式检测平台。该多检测算法融合了眼睛和嘴巴的疲劳特征

当某一特征的检测受到影响时可以使用另外的特征进行疲劳状态的判定

较传统的单一特征疲劳检测算法拥有更高的检测效率。实验结果表明:系统的算法简单、可靠、实时性强。

Abstract

Driving fatigue is one of the most important factors in traffic accident

in order to real-time and effectively detect driving fatigue

an algorithm fusing multiple fatigue characteristics is proposed for fatigue state judgement is designed

and build a vehicle FPGA-based embedded test platform.The multiple detection algorithm fuses

fatigue features of eyes and mouth

when a feature detection is affected

other features can be used for judgment of fatigue state.Compared with traditional single feature fatigue detection algorithm

it has higher detection efficiency.Experimental result show that the system algorithm is simple

reliability and real-time.

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references

基于视觉信息融合的驾驶员疲劳监测方法综述 [J]. 张恒,刘艳丽. 信息技术 . 2008(06)

基于PERCLOS的驾驶疲劳检测系统设计 [D]. 吴康华. 浙江大学 2008

汽车驾驶员疲劳实时识别与监测系统研究 [D]. 黄博学. 长沙理工大学 2008

Robust Real-Time Face Detection [J] . Paul Viola,Michael J. Jones. International Journal of Computer Vision . 2004 (2)

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