基于人脸识别技术的驾驶员疲劳监测系统 中英文双语外文文献翻译成品

1、外文标题：The Driver Fatigue Monitoring System Based on Face Recognition Technology外文作者：Xiao-qing Luo , Rong Hu, Tian-e Fan文献出处:International Conference on Intelligent Control & Information Processing英文2486单词， 12908字符，中文3769汉字。此文档是外文翻译成品，无需调整复杂的格式哦！下载之后直接可用，方便快捷！价格不贵。原文：The Driver Fatigue Monitoring System Based on Face Recognition TechnologyXiao-qing Luo , Rong Hu, Tian-e FanAbstractThis paper uses different algorithms, which are called AdaBoost algorithm and the difference between infrared frames a

2、lgorithm, to locate the precise position of the eyes in different light environment of driving. We identify the eyes status by extracting the characteristic parameters of eyes and detect fatigue based on the method of PERCLOS. At the same time, tfurther test the drivers fatigue, we use the Local Binary Patter (LBP) algorithm to detect the yawning as an aided detection. The results of the experiment show that algorithm ensures the accuracy of the system and it can achieve the requirement of non c

3、ontact type, different lighting conditions and real-time detection.Keywords:Driver fatigue; Yawning detection; Eye detection; PERCLOS; AdaBoost.IntroductionNowadays, fatigue driving is one of the main reasons for traffic accidents 1. Its reported that there were 3906164 traffic accidents in 2010 in our country. Among them, 92% of accident deaths were caused by motor vehicle driver speeding, while most of accident deaths caused by the fatigue driving roses 1% 2. At present, there are already some

4、 methods of fatigue testing such as testing through the position of head, EEG, EKG, eye blinking, PERCLOS and so on 3. And as a non-contact method, PERCLOS method is able to reflect peoples situation of eyelids and their degree of fatigue when they are sleepy, but its easy to be influenced by the lighting. This paper analyzes the brightness of picture which is taken by CCD camera to estimate day or night. We utilize AdaBoost algorithm to locate peoples faces and eyes in the daytime, while at nig

5、ht we use infrared frame difference to test their eyes 4. We judge drivers condition of eyes through extracting characteristic parameters of the eyes, including the ratio of high and wide and eyelid curvature. And then adopt the method of PERCLOS to test drivers fatigued degree. In addition, after locating drivers eyes, we locate drivers mouth according to their characters of faces. Then use LBP algorithm to test yawn and judge drivers fatigued state. The study on fatigued driving system has a s

6、ignificance on the prevention of traffic accidents 5.System frameworkThe framework of driver fatigue warning system can be seen in Figure 1, including the infrared light source CCD sensor camera which can control the near-far, the image pre- processing module, module of fatigue detection and alarm devices 6. CCD camera is being introduced to pick up drivers face image. And the image pre-processing module is used to obtain the image histogram equalization, smoothing pre-processing operation. Fati

7、gue detection module is to calculate eyes closed extent by extracting characteristic parameters of eyes and measure the P80 (the eye status is determined to close when the closure degree is greater than 80 percent) which was got by using PERCLOS method to detect drivers fatigue. Alarm device is used to determine driver fatigue, if driver is tired, an alarm signal will be found 7.Image processingThe processing system is shown in Figure 2. The system estimates the image daytime or night according

8、to the brightness of it. When the brightness is greater than a certain threshold (45), it is the daytime image and daytime mode algorithm is used for image processing, to the contrary, the processing algorithm using the night mode.Image pre-processingThe adaptability of the algorithm and the accuracy of detection will be affected by many factors if direct detection due to the collected images is influenced by the illumination, background, noise and other factors. Therefore, we have to pre-proces

9、s these images. In order to efficiently distinguish between foreground and background, in the stage of image pre-processing, lighting compensation and image histogram equalization of treatment are done first to enhance the contrast of image. Meanwhile, to eliminate the influence of noise, the operation of image median filtering can not only removes isolated point noise, but also effectively protects the image boundary information; In addition, the controllable distance infrared CCD camera is applied to capture images under low light conditions 7.Process in day modeEyes location and face detectionThis paper proposes a face detection method named AdaBoost to detect eyes and face with rectangular characteristics. This method is composed of integral image, AdaBoost algorithm and cascade detector 8. Also it can solve the complexity of face and eye detection problem well. At the same time, the AdaBo

《基于人脸识别技术的驾驶员疲劳监测系统 中英文双语外文文献翻译成品》由会员从****越分享，可在线阅读，更多相关《基于人脸识别技术的驾驶员疲劳监测系统 中英文双语外文文献翻译成品》请在金锄头文库上搜索。