计算机科学
人工智能
特征(语言学)
计算机视觉
面子(社会学概念)
特征提取
人脸检测
人工神经网络
模式识别(心理学)
模拟
面部识别系统
社会科学
语言学
哲学
社会学
作者
Yimin Zhang,Xianwei Han,Wei Gao,Yunliang Hu
标识
DOI:10.1142/s0218001421500348
摘要
Fatigue driving is one of the main causes of traffic accidents. In recent years, considerable attention has been paid to fatigue detection systems, which is an important solution for preventing fatigue driving. In order to prevent and reduce fatigue driving, a driver fatigue detection system based on computer vision is proposed. In this system, an improved face detection method is used to detect the driver’s face from the image obtained by a charge coupled device (CCD) camera. Then, the feature points of the eyes and mouth are located by an ensemble of regression trees. Next, fatigue characteristic parameters are calculated by the improved percentage of eyelid closure over the pupil over time algorithm. Finally, the state of drivers is evaluated by using a fuzzy neural network. The system can effectively monitor and remind the state of drivers so as to significantly avoid or decrease the occurrence of traffic accidents. The experimental results show that the system is of wonderful real-time performance and accurate recognition rate, so it meets the requirements of practicality in driver fatigue detection greatly.
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