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胡习之,黄冰瑜. 基于面部特征分析的疲劳驾驶检测方法[J]. 科学技术与工程, 2021, 21(4): 1629-1636.
HU Xi-zhi,HUANG Bing-yu.Fatigue Driving Detection System Based on Face Feature Analyze[J].Science Technology and Engineering,2021,21(4):1629-1636.
基于面部特征分析的疲劳驾驶检测方法
Fatigue Driving Detection System Based on Face Feature Analyze
投稿时间:2020-05-01  修订日期:2020-11-18
DOI:
中文关键词:  疲劳驾驶检测  人脸检测  疲劳特征参数  PERCLOS
英文关键词:fatigue driving detection  face detection  fatigue feature parameters  PERCLOS
基金项目:
     
作者单位
胡习之 华南理工大学机械与汽车工程学院
黄冰瑜 华南理工大学机械与汽车工程学院
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中文摘要:
      为避免疲劳驾驶,通过提取面部疲劳特征参数的方法研究了驾驶员疲劳检测技术。对SSD目标检测算法及CamShift跟踪算法进行优化,以检测人脸区域。利用特征点定位提取面部疲劳特征参数,并基于PERCLOS准则设定疲劳阈值和疲劳检测策略。在实车样本集上进行试验,结果表明:优化的人脸区域定位方法对光线变化、类肤色干扰的鲁棒性更强;所提取的疲劳特征参数能有效反映驾驶员疲劳状态,平均识别准确率达到了92.2%。
英文摘要:
      In order to avoid fatigue driving, the driver fatigue detection technique was studied by extracting the facial fatigue feature parameters. A face detection method combining SSD target detection algorithm and CamShift tracking algorithm was designed. The characteristic parameters of facial fatigue were extracted by using the feature points. Based on PERCLOS criterion, the fatigue threshold and fatigue detection strategy were set. The system detection effect was evaluated on the real vehicle sample set, and the results showed that: the optimized face area localization method has stronger robustness to light change and skin-color interference; the extracted fatigue characteristic parameters can effectively reflect the fatigue state of the driver, with an average recognition accuracy of 92.2%.
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