CN103366506A - Device and method for automatically monitoring telephone call behavior of driver when driving - Google Patents
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Abstract
本发明涉及一种驾驶员行车途中接打手机行为的自动监控装置及方法,属于智能交通领域和辅助驾驶领域。该装置包括图像获取装置,计算装置,警告装置以及无线传输装置;首先获取驾驶员头部及附近区域图像,其次通过肤色检测得到驾驶员的脸部及手部在图像中的位置,通过支持向量机进行分类,从而确定驾驶员是否在接打手机。若接打手机,则对驾驶员发出警告;若警告无用,则将驾驶员接打手机的图像通过无线网络上传到交通局的监控中心,作为其违法的证据。本发明可以有效监控司机违法行为,减轻了执法人员的工作强度,提高工作效率,从而减少交通事故的发生率。
The invention relates to an automatic monitoring device and method for a driver's mobile phone behavior while driving, and belongs to the field of intelligent transportation and assisted driving. The device includes an image acquisition device, a computing device, a warning device and a wireless transmission device; firstly, the image of the driver's head and the surrounding area is obtained; secondly, the position of the driver's face and hands in the image is obtained through skin color detection; Classify the mobile phone to determine whether the driver is answering or calling the mobile phone. If the mobile phone is connected, the driver will be warned; if the warning is useless, the image of the driver’s mobile phone will be uploaded to the monitoring center of the traffic bureau through the wireless network as evidence of his violation. The invention can effectively monitor illegal behaviors of drivers, reduce the work intensity of law enforcement personnel, improve work efficiency, and thereby reduce the occurrence rate of traffic accidents.
Description
技术领域technical field
本发明涉及智能交通领域和辅助驾驶领域。The invention relates to the fields of intelligent transportation and assisted driving.
背景技术Background technique
随着手机使用的普及,驾驶员在一边开车一边拨打或接听手机的行为随处可见。由于驾驶员在接打手机时,往往是单手操纵方向盘,不能很好地控制车辆;更重要的是,接打手机会分散驾驶员的注意力,一旦遇到突发事件,往往反应不及,极易造成交通事故。研究表明,开车时使用手机,大脑的反应速度比酒后驾车时慢30%,开车时使用手机发生车祸的风险比正常驾驶时高4倍以上。有70%的致命交通事故是司机注意力不集中造成的,而手机又是造成注意力不集中的主要原因之一。鉴于开车接打手机对交通安全的危害性,目前世界上已有约50个国家和地区明令禁止司机在驾车过程中接打手机。我国最新的《道路交通安全法实施条例》也明确规定“驾驶员在行驶途中拨打或接听手机的,记3分,罚款100元”。With the popularization of mobile phone use, the behavior of drivers dialing or answering mobile phones while driving can be seen everywhere. Because the driver often controls the steering wheel with one hand when answering and calling the mobile phone, he cannot control the vehicle well; more importantly, answering and calling the mobile phone will distract the driver's attention. Very likely to cause traffic accidents. Studies have shown that when using a mobile phone while driving, the brain's reaction speed is 30% slower than that of drunk driving, and the risk of a car accident when using a mobile phone while driving is more than 4 times higher than that of normal driving. 70% of fatal traffic accidents are caused by drivers' inattention, and mobile phones are one of the main reasons for inattention. In view of the harmfulness of using mobile phones while driving to traffic safety, there are currently about 50 countries and regions in the world that prohibit drivers from using mobile phones while driving. my country's latest "Regulations for the Implementation of the Road Traffic Safety Law" also clearly stipulates that "if a driver calls or answers a mobile phone while driving, he will be given 3 points and a fine of 100 yuan."
但是由于该行为发生在高速行驶的汽车上,在车外很难捕捉。目前驾驶员开车接打手机行为的监控主要有三种方法。第一种是执法人员现场执法,但是执法人员一般只出现在路口等少数区域,因此这种方法具有很大的局限性。第二种是车外摄像头监控。这种方式可以拍到驾驶员开车时使用手机的行为,虽然监控范围与第一种方法相比有所扩大,但是也只限制在摄像头所能监控到的范围,在大部分区域还是监控不到该行为的。此外,该方法还需要监控人员时刻盯着监控器判断该违法行为,工作强度大,效率低,而且在夜间效率更低。第三种是在固定区域安装指向性天线监控来自行驶中的车辆上的手机信号,若是正在通话中的信号则启动影像设备进行现场取证。该方法虽然可以起到自动监控的功能,但是会拍摄所有检测到有正在通话的手机信号的车辆,而此时不一定是司机在打电话,也可能是车内别的人在通话,会有很多误检的情况。在后两种方法中摄像头都是安在车外的,有时会因为天气或者遮挡等原因使得拍摄到的图片不能很清晰的看到车内情况,会有漏检及误检发生。However, since this behavior occurs in a car traveling at high speed, it is difficult to capture outside the car. At present, there are mainly three methods for monitoring the driver's mobile phone behavior while driving. The first is law enforcement personnel on-the-spot enforcement, but law enforcement personnel generally only appear in a few areas such as intersections, so this method has great limitations. The second is the camera monitoring outside the car. This method can capture the behavior of the driver using the mobile phone while driving. Although the monitoring range has been expanded compared with the first method, it is only limited to the range that the camera can monitor, and it cannot be monitored in most areas. the behavior. In addition, this method also requires monitoring personnel to stare at the monitor all the time to judge the illegal act, which has high work intensity and low efficiency, and the efficiency is even lower at night. The third is to install a directional antenna in a fixed area to monitor the mobile phone signal from a moving vehicle, and if it is a signal in a call, start the imaging device for on-site evidence collection. Although this method can play the function of automatic monitoring, it will take pictures of all the vehicles that detect the signal of the mobile phone that is talking. At this time, it is not necessarily the driver who is calling, or someone else in the car is talking. Lots of false positives. In the latter two methods, the cameras are all installed outside the car. Sometimes the captured pictures cannot clearly see the situation inside the car due to reasons such as weather or occlusion, and there will be missed detection and false detection.
基于以上原因,“行车途中接打手机”行为无法得到有效的监控,使得这种行为随处可见,对交通安全造成了很大的隐患。目前,还没有基于车内摄像头的对驾驶员行车途中接打手机行为进行自动监控的装置。Based on the above reasons, the behavior of "calling and answering mobile phones while driving" cannot be effectively monitored, making this behavior everywhere and causing great hidden dangers to traffic safety. At present, there is no device for automatically monitoring the driver's mobile phone behavior based on the in-vehicle camera.
发明内容Contents of the invention
为解决上述问题,本发明提供了一种驾驶员行车途中接打手机行为的自动监控装置及方法。通过车内摄像头采集驾驶员头部及附近区域图像,利用图像处理技术和模式识别方法对驾驶员行车途中接打手机的行为进行自动识别,并将其违规图片拍摄下来联网上传到交通局的监控中心,作为违规证据。本发明提供了一种对驾驶员行车途中接打手机行为进行自动监控的方法。可大大降低执法强度,提高执法效率,有效的避免因驾驶员行车途中拨打或接听手机行为造成的交通事故。而且本发明将摄像头安装在车内的前挡风玻璃上,可以很清晰的拍摄到司机的行为,且不需其他电子器件辅助,不会影响到司机的正常行车。In order to solve the above problems, the present invention provides an automatic monitoring device and method for the driver's mobile phone behavior while driving. Collect images of the driver's head and nearby areas through the camera in the car, use image processing technology and pattern recognition methods to automatically identify the driver's behavior of answering and calling mobile phones while driving, and take pictures of violations and upload them to the monitoring of the traffic bureau Center, as evidence of violation. The invention provides a method for automatically monitoring the driver's behavior of receiving and calling mobile phones during driving. It can greatly reduce the intensity of law enforcement, improve the efficiency of law enforcement, and effectively avoid traffic accidents caused by drivers dialing or answering mobile phones while driving. Moreover, the present invention installs the camera on the front windshield in the car, which can clearly photograph the behavior of the driver without the assistance of other electronic devices and will not affect the normal driving of the driver.
一种驾驶员行车途中接打手机行为的自动监控装置,包括:图像获取装置,计算装置,警告装置以及无线传输装置;其中,An automatic monitoring device for the driver's mobile phone behavior during driving, including: an image acquisition device, a computing device, a warning device and a wireless transmission device; wherein,
图像获取装置采用固定于车内前挡风玻璃上的摄像机获取驾驶员头部及附近区域图像,并将图像传送给计算装置;The image acquisition device uses a camera fixed on the front windshield in the vehicle to acquire images of the driver's head and nearby areas, and transmits the images to the computing device;
计算装置通过肤色检测得到驾驶员的脸部及手部在图像中的位置,计算脸部及手部区域的梯度直方图特征以及驾驶员的唇部形状特征,得到驾驶员使用手机状态下和没有使用手机状态下的特征,通过支持向量机进行分类,从而确定驾驶员是否在驾驶过程中接打手机,并将驾驶员是否接打手机的信息传递给警告装置;The computing device obtains the position of the driver's face and hands in the image through skin color detection, calculates the gradient histogram features of the face and hand regions and the driver's lip shape features, and obtains the driver's state of using a mobile phone and without it. Use the characteristics of the mobile phone state, classify through the support vector machine, so as to determine whether the driver is answering and calling the mobile phone during driving, and pass the information of whether the driver is answering and calling the mobile phone to the warning device;
警告装置在接收到计算装置发来的驾驶员正在接打手机信息后,对驾驶员发出警告,如果发出警告后依然接收到计算装置发来的驾驶员正在接打手机的信息,则发送信号到无线传输装置;The warning device sends a warning to the driver after receiving the information that the driver is receiving and calling the mobile phone from the computing device, and if the driver still receives the information that the driver is receiving and calling the mobile phone from the computing device after sending the warning, then send a signal to wireless transmission device;
无线传输装置将驾驶员接打手机的图像通过无线网络上传到交通局的监控中心,作为其违法的证据。The wireless transmission device uploads the image of the driver calling and calling the mobile phone to the monitoring center of the traffic bureau through the wireless network, as evidence of his violation of the law.
一种驾驶员行车途中接打手机行为的自动监控方法,实现步骤如下:An automatic monitoring method for a driver's mobile phone behavior while driving, the implementation steps are as follows:
步骤一:当车辆发动机启动时监控装置自动开启,装置进行自检操作,检查拍摄到的视频画面中是否有人脸,并且人脸是否处于特定的区域内(防止司机移动或遮挡装置),若以上条件都满足,则方向盘解锁;否则方向盘处于锁定状态,驾驶员不能驾驶车辆。Step 1: When the vehicle engine is started, the monitoring device is automatically turned on, and the device performs a self-check operation to check whether there is a human face in the captured video screen, and whether the face is in a specific area (to prevent the driver from moving or blocking the device), if the above If the conditions are met, the steering wheel is unlocked; otherwise, the steering wheel is locked and the driver cannot drive the vehicle.
步骤二:装置正常启动后,开始监控头部区域图像,若在车辆行驶的过程中发现有驾驶员接打手机姿势发生超过一定时间,并同时伴有唇部动作,则判定其在接打手机。Step 2: After the device starts normally, it starts to monitor the image of the head area. If it is found that the driver's gesture of answering and calling the mobile phone exceeds a certain period of time, accompanied by lip movements, it is determined that the driver is answering and calling the mobile phone. .
步骤三:警报装置发生警报,如果在警报发出3秒钟后,司机仍然没有停止使用手机,则摄像头将其使用手机的图像通过网络上传到交通局的监控中心,作为其违法的证据,方便执法人员对该违法行为进行处理。Step 3: The alarm device generates an alarm. If the driver still does not stop using the mobile phone 3 seconds after the alarm is issued, the camera will upload the image of the driver using the mobile phone to the monitoring center of the Traffic Bureau through the network, as evidence of his violation, and to facilitate law enforcement personnel to deal with the violation.
步骤四:该装置只在车辆行驶途中开启,当车辆停止时,装置自动停止工作。Step 4: The device is only turned on when the vehicle is driving, and when the vehicle stops, the device automatically stops working.
本发明的优点:Advantages of the present invention:
1.可以实时监控到驾驶员的行车途中接打手机的违规行为。1. It can monitor in real time the violation of the driver's mobile phone calls while driving.
2.可以自动地将违规记录传递到监控中心,减轻了执法人员的工作负担,提高工作效率。2. It can automatically transfer violation records to the monitoring center, which reduces the workload of law enforcement personnel and improves work efficiency.
3.该装置是自动运行的,不需要驾驶员的操作,简单易用。3. The device is automatic and does not require the driver's operation, which is simple and easy to use.
4.该装置是强制安装的,并可保证该功能的实现,可以有效监控司机违法行为,减少该违法行为,从而减少交通事故的发生率。4. The device is mandatory and can guarantee the realization of this function. It can effectively monitor the driver's illegal behavior and reduce the illegal behavior, thereby reducing the incidence of traffic accidents.
5.摄像头是安装在车内的,不受外界环境如天气,遮挡等因素的影响,可以拍摄到清晰的图像。5. The camera is installed in the car and can capture clear images without being affected by the external environment such as weather, occlusion and other factors.
附图说明Description of drawings
图1为本发明中驾驶员行车途中接打手机行为的监控、警告及自动取证的流程图;Fig. 1 is the flow chart of the monitoring, warning and automatic evidence collection of the driver's mobile phone behavior on the way of driving in the present invention;
图2为本发明中用于驾驶员人脸检测的矩形特征。Fig. 2 is the rectangular feature used for driver's face detection in the present invention.
具体实施方式Detailed ways
本发明的核心思路是:驾驶员在接打手机时,肯定会有手持手机靠近耳部的动作,并伴有唇部运动。通过视频分析,判断是否产生这些行为,从而判断其是否在接打手机。一旦确定其违法行为,在警告无效的情况下,立刻将其违规图像传送给监控中心,并形成一条违规记录,便于执法人员收集证据。The core idea of the present invention is: when the driver is answering and calling the mobile phone, there must be an action of holding the mobile phone close to the ear, accompanied by lip movement. Through video analysis, it is judged whether these behaviors occur, so as to judge whether it is making or receiving a mobile phone. Once the illegal behavior is determined, if the warning is invalid, the image of the violation will be sent to the monitoring center immediately, and a violation record will be formed, which is convenient for law enforcement officers to collect evidence.
本发明的自动监控装置,包括:图像获取装置,计算装置,警告装置以及无线传输装置;其中,The automatic monitoring device of the present invention includes: an image acquisition device, a computing device, a warning device and a wireless transmission device; wherein,
图像获取装置采用固定于车内前挡风玻璃上的摄像机获取驾驶员头部及附近区域图像;The image acquisition device uses a camera fixed on the front windshield of the vehicle to acquire images of the driver's head and nearby areas;
计算装置通过肤色检测得到驾驶员的脸部及手部在图像中的位置,计算脸部及手部区域的梯度直方图特征以及驾驶员的唇部形状特征,得到驾驶员使用手机状态下和没有使用手机状态下的特征,通过支持向量机进行分类,从而确定驾驶员是否在驾驶过程中接打手机;The computing device obtains the position of the driver's face and hands in the image through skin color detection, calculates the gradient histogram features of the face and hand regions and the driver's lip shape features, and obtains the driver's state of using a mobile phone and without it. Using the characteristics of the mobile phone state, classify through the support vector machine to determine whether the driver is answering and calling the mobile phone during driving;
警告装置在计算装置确定驾驶员在接打手机后,对驾驶员发出警告;The warning device issues a warning to the driver after the computing device determines that the driver is answering and calling the mobile phone;
无线传输装置将驾驶员接打手机的图像通过无线网络上传到交通局的监控中心,作为其违法的证据。The wireless transmission device uploads the image of the driver calling and calling the mobile phone to the monitoring center of the traffic bureau through the wireless network, as evidence of his violation of the law.
本发明中基于车内摄像头的驾驶员行车途中接打手机行为监控、警告及自动取证的流程图如图1所示,具体实施步骤如下:In the present invention, the flow chart of monitoring, warning and automatic evidence collection based on the driver's mobile phone behavior monitoring, warning and automatic evidence collection on the way of driving based on the camera in the car, the specific implementation steps are as follows:
步骤一:当车辆发动机启动时监控装置自动开启,装置进行自检操作,检查拍摄到的视频画面中是否有人脸,并且人脸是否处于特定的区域内(防止司机移动或遮挡装置),若以上条件都满足,则方向盘解锁;否则方向盘处于锁定状态,驾驶员不能驾驶车辆。Step 1: When the vehicle engine is started, the monitoring device is automatically turned on, and the device performs a self-check operation to check whether there is a human face in the captured video screen, and whether the face is in a specific area (to prevent the driver from moving or blocking the device), if the above If the conditions are met, the steering wheel is unlocked; otherwise, the steering wheel is locked and the driver cannot drive the vehicle.
采用基于AdaBoost的人脸检测方法进行驾驶员人脸的定位。该方法以矩形特征为依据来构造弱分类器,再用AdaBoost方法挑选出少量关键特征,对相应的弱分类器进行加权求和从而构建出强分类器,并将其作为最终分类器用于人脸检测。其中,每个矩形特征由2-3个矩形组成,如图2所示,其值为白色矩形内的像素值之和减去黑色矩形内的像素值之和。The face detection method based on AdaBoost is used to locate the driver's face. This method constructs a weak classifier based on rectangular features, and then uses the AdaBoost method to select a small number of key features, and weights and sums the corresponding weak classifiers to construct a strong classifier, which is used as the final classifier for the face detection. Among them, each rectangle feature is composed of 2-3 rectangles, as shown in Figure 2, its value is the sum of the pixel values in the white rectangle minus the sum of the pixel values in the black rectangle.
每个弱分类器由一个矩形特征组成,强分类器的的训练流程如下:Each weak classifier consists of a rectangular feature, and the training process of the strong classifier is as follows:
(1)给定训练数据(x1,y1),...(xn,yn),其中yi=0表示负样本,yi=1表示正样本,n为训练样本的个数。(1) Given training data (x 1 ,y 1 ),...(x n ,y n ), where y i =0 represents negative samples, y i =1 represents positive samples, and n is the number of training samples .
(2)初始化权值,yi=0时yi=1时m,l分别是负样本和正样本的个数。(2) Initialize the weight value, when y i =0 when y i =1 m and l are the number of negative samples and positive samples respectively.
(3)对应t=1,...,T:(3) Corresponding to t=1,...,T:
A.归一化权值
B.对与每一个特征j,训练弱分类器hj,此若分类器的误差为εj=∑iwi|hj(xi)-yi|B. For each feature j, train a weak classifier h j , if the error of the classifier is ε j =∑ i w i |h j (xi ) -y i |
C.选择具有最小误差的分类器ht C. Choose the classifier h t with the smallest error
D.更新权值其中ei=0如果xi被正确分类,否则ei=1,
(4)则最终的强分类器为(4) Then the final strong classifier is
得到强分类器后,使用强分类器对图像进行扫描,得到驾驶员的人脸位置,如果人脸在图像的中心区域,则装置正常运行。自检成功,方向盘解锁,驾驶员可以开动车辆。After getting the strong classifier, use the strong classifier to scan the image to get the position of the driver's face. If the face is in the center of the image, the device works normally. The self-test is successful, the steering wheel is unlocked, and the driver can start the vehicle.
步骤二:装置正常启动后,在车辆行驶过程中自动监控头部区域图像,若发现有驾驶员接打手机姿势发生超过一定时间,并同时伴有唇部动作,则判定其在使用手机。Step 2: After the device starts up normally, it automatically monitors the image of the head area during the driving of the vehicle. If it is found that the driver's gesture of answering and calling the mobile phone exceeds a certain period of time, accompanied by lip movements, it is determined that the driver is using the mobile phone.
由于驾驶员正常驾驶状态和使用手机时手放在耳部的状态相比有很大的差别。因此我们采用训练SVM分类器的方式判断驾驶员是否在接打手机。由于驾驶员在说话和不说话时,唇部状态有明显的差异,因此判断驾驶员唇部是否动作也采用训练SVM分类器的方式。综合以上两个线索,驾驶员做出了接打手机的姿势超过一定时间,并且其间伴有唇部动作,则判定驾驶员是在接打手机。Because there is a big difference between the driver's normal driving state and the state of putting his hands on his ears when using a mobile phone. Therefore, we use the method of training the SVM classifier to judge whether the driver is answering or calling the mobile phone. Since there are obvious differences in the state of the lips of the driver when he is speaking and not speaking, the method of training the SVM classifier is also used to judge whether the driver's lips are moving. Based on the above two clues, if the driver has made the gesture of answering and calling the mobile phone for more than a certain period of time, and there is lip movement during the period, it is determined that the driver is answering and calling the mobile phone.
1)提取驾驶员头部区域的HOG特征1) Extract the HOG features of the driver's head area
训练分类器所使用的特征均为HOG特征。HOG即histogram of orientedgradient(梯度方向直方图),是用于目标检测的特征描述子,它将图像局部出现的方向梯度次数进行计算。该方法通过将整幅图像分割成小的连接区域(称为cells),每个cell生成一个方向梯度直方图,这些直方图的组合可表示出所检测目标的描述子。为改善准确率,可以将图像中一个较大区域(称为block)中的所有cells归一化。通过归一化过程完成了更好的照射/阴影不变性。The features used to train the classifier are all HOG features. HOG is histogram of oriented gradient (histogram of gradient direction), which is a feature descriptor used for target detection. It calculates the number of directional gradients that appear locally in the image. The method divides the entire image into small connected regions (called cells), each cell generates a histogram of oriented gradients, and the combination of these histograms can represent the descriptor of the detected object. To improve accuracy, it is possible to normalize all cells within a larger region (called a block) in the image. Better lighting/shading invariance is done through the normalization process.
HOG特征提取方法如下:The HOG feature extraction method is as follows:
(1)将图像转化为灰度图像。(1) Convert the image to a grayscale image.
(2)将图像划分成小cells(eg:2*2)。(2) Divide the image into small cells (eg: 2*2).
(3)计算每个cell中每个像素的梯度。(3) Calculate the gradient of each pixel in each cell.
梯度大小:
梯度方向:Ang(x,y)=arctan((I(x+1,y)-I(x-1,y))/(I(x,y+1)-I(x,y-1)))Gradient direction: Ang(x,y)=arctan((I(x+1,y)-I(x-1,y))/(I(x,y+1)-I(x,y-1) ))
(4)归一化每个block中的所有cells。采用L2-norm进行归一化:(4) Normalize all cells in each block. Normalize with L2-norm:
L2-norm:
(5)生成HOG特征。计算检测窗口中所有block中的HOG特征,并将其连接为最终的特征向量供分类使用。(5) Generate HOG features. Calculate the HOG features in all blocks in the detection window and concatenate them into the final feature vector for classification.
2)使用SVM对HOG特征进行分类2) Use SVM to classify HOG features
提取完驾驶员头部区域的HOG特征后,将其作为SVM分类器的输入,进行分类,以判断驾驶员的头部姿态。After extracting the HOG feature of the driver's head area, it is used as the input of the SVM classifier for classification to judge the driver's head posture.
SVM即Support Vector Machine(支持向量机),它是一种监督式学习的方法,在解决小样本、非线性及高维模式识别中表现出许多特有的优势。SVM基于结构风险最小化理论之上在特征空间中建构最优分割超平面,使得分类器得到全局最优化,并且在整个样本空间的期望风险以某个概率满足一定上界。SVM stands for Support Vector Machine (Support Vector Machine), which is a supervised learning method that shows many unique advantages in solving small sample, nonlinear and high-dimensional pattern recognition. Based on the structural risk minimization theory, SVM constructs the optimal segmentation hyperplane in the feature space, so that the classifier is globally optimized, and the expected risk in the entire sample space meets a certain upper bound with a certain probability.
假设超平面的数学形式为:w·x-b=0。其中x是超平面上的点,w是垂直于超平面的向量。(x(i),y(i))为训练样本。x(i)为训练样本的特征输入;y(i)为其对应标签,其中y(i)∈{1,-1}。则在线性可分的情况下,最优超平面可以通过解下面的二次优化问题来获得:Assume that the mathematical form of the hyperplane is: w·xb=0. where x is a point on the hyperplane and w is a vector perpendicular to the hyperplane. (x (i) , y (i) ) are training samples. x (i) is the feature input of the training sample; y (i) is its corresponding label, where y (i) ∈ {1,-1}. Then in the case of linear separability, the optimal hyperplane can be obtained by solving the following quadratic optimization problem:
满足约束条件:y(i)(wTx(i)+b)≥1,i=1,2,...,mSatisfy the constraints: y (i) (w T x (i) +b)≥1,i=1,2,...,m
3)判断驾驶员唇部状态3) Judging the state of the driver's lips
判断驾驶员唇部状态的过程为:The process of judging the state of the driver's lips is as follows:
1.通过Adaboost学习算法检测出人脸位置1. Detect the position of the face through the Adaboost learning algorithm
2.嘴唇位置粗定位。根据先验知识,嘴唇位于人脸的下半部分。2. Coarse positioning of the lip position. According to prior knowledge, lips are located in the lower half of the human face.
3.嘴唇形状及位置确定。训练皮肤颜色和唇部颜色,分别确定其颜色范围,利用Fisher线性分类器将皮肤颜色和唇部颜色区分开,分割出嘴部区域。3. Determine the shape and position of the lips. Train the skin color and lip color, determine their color range respectively, use Fisher linear classifier to distinguish the skin color and lip color, and segment the mouth area.
4.消除噪声。通过对上一步分割出的嘴部区域进行先腐蚀后膨胀的方法,消除小的连通区域,达到去除噪声的目的。去除噪声后的区域就是嘴部区域。4. Eliminate noise. By first corroding and then expanding the mouth area segmented in the previous step, the small connected areas are eliminated to achieve the purpose of noise removal. The area after noise removal is the mouth area.
5.嘴部轮廓确定。对上一步检测出的嘴部区域进行水平和垂直投影,得到嘴部轮廓。5. The contour of the mouth is determined. The mouth area detected in the previous step is horizontally and vertically projected to obtain the mouth contour.
6.特征提取。根据嘴部轮廓计算出嘴部区域的最大宽度Wmax,最大高度Hmax,及上嘴唇与下嘴唇之间的高度Hm。这几个值在人说话和不说话时有明显不同,因此取为特征。F=(Wamx,Hmax,Hm).6. Feature extraction. Calculate the maximum width W max , the maximum height H max , and the height H m between the upper lip and the lower lip of the mouth region according to the mouth contour. These values are obviously different when people are speaking and not speaking, so they are taken as features. F=(W amx ,H max ,H m ).
7.训练SVM分类器对唇部特征进行分类,来判别驾驶员的嘴部状态。4)判断驾驶员是否在接打手机7. Train the SVM classifier to classify the lip features to determine the state of the driver's mouth. 4) Judging whether the driver is answering or calling the mobile phone
当使用SVM对驾驶员头部区域的HOG特征进行分类,判断其属于接打手机的姿势,同时判断驾驶员唇部状态为说话状态,并且此类状况持续时间超过给定阈值时,则判断驾驶员在接打手机。When using SVM to classify the HOG features of the driver's head area, it is judged that it belongs to the gesture of answering and calling the mobile phone, and at the same time it is judged that the state of the driver's lips is speaking, and when the duration of this situation exceeds a given threshold, it is judged that the driving The staff is answering the phone.
步骤三:警报装置发出警报,如果在警报发出3秒钟后,司机仍然没有停止使用手机,则无线传输装置将其使用手机的图像通过网络上传到执法人员的监控中心,作为其违法的证据。并将其违法行为,时间等内容记录下来,方便执法人员对该违法行为进行处理。Step 3: The alarm device sends out an alarm. If the driver still does not stop using the mobile phone after 3 seconds of the alarm, the wireless transmission device uploads the image of the driver using the mobile phone to the monitoring center of law enforcement officers through the network as evidence of his violation. And record its illegal behavior, time and other content, so that law enforcement officers can deal with the illegal behavior.
步骤四:该装置只在车辆行驶途中开启,当车辆停止时,装置自动停止工作。Step 4: The device is only turned on when the vehicle is driving, and when the vehicle stops, the device automatically stops working.
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