基于机器视觉的驾驶员后视镜查看行为识别系统设计
发布时间:2019-05-26 21:20
【摘要】:统计数据表明,25%~30%的交通事故与驾驶员的警觉状态直接相关,其中车辆转弯、并线、变更车道等转向操控过程是交通事故的主要发生场合之一,尤其常见于驾驶员未注意车辆转向侧后方交通信息的情况。驾驶员后视镜查看行为的实时检测和必要提醒有利于降低此类交通事故的发生概率。本文基于机器视觉和图像处理技术对该行为进行探索和研究,提出了与之相关的检测方法和技术方案,并采用大量的实验和算例进行验证,最终开发出驾驶员后视镜查看行为检测系统。主要工作和研究成果包括:(1)在对大量国内外相关技术和文献调研的基础上,针对课题中可能遇到的问题,提出了一种仅以驾驶员脸颈部轮廓作为处理目标的驾驶员后视镜查看行为检测方法。算法任务量小、实时性好、鲁棒性高。(2)基于驾驶员行为特性,首先提出一种驾驶员脸颈区域静态识别定位算法,用于在车辆启动时,完成驾驶员脸颈皮肤在当前光源条件下的灰度均值学习和脸颈区域静态搜索识别。然后提出一种驾驶员脸颈区域动态识别定位算法,用于在车辆行驶时,完成驾驶员脸颈皮肤灰度均值学习和脸颈区域快速跟踪识别。最后在此基础上提取驾驶员脸颈可见皮肤轮廓并定义了以颈部基点垂线划分的左右面积比特征参数。图像处理结果表明,算法具有较好的自适应学习能力和抗干扰能力。(3)针对驾驶员脸型差异、摄像头安装位置不同,以及驾驶员发型、佩戴物等等干扰情况而导致基准特征参数的不同,论文结合驾驶眼动凝视数据分析揭示了特征参数的累积概率局部峰值定律,据此提出一种后视镜查看行为的阈值判定原理。当后视镜观察行为获得确认后,及时利用本次查看过程中的所有参数值更新累积概率并重新进行参数估计。实验数据表明,有效的后视镜查看数据更新累积概率可完成参数的自适应调整。(4)检测系统体积小,易于推广。系统在基于树莓派3代微处理器和嵌入式Linux系统平台上,用户界面设计使用Qt,图像接口函数使用图像处理开源库OpenCV。检测结果表明,系统具有良好的实时性和普适能力。
[Abstract]:The statistical data show that 25% of the traffic accidents are directly related to the alert state of the driver, in which the turning of the vehicle, parallel lane, lane change and other steering and control processes are one of the main situations of traffic accidents. It is especially common that the driver does not pay attention to the traffic information behind the steering side of the vehicle. The real-time detection and necessary reminder of driver's rearview mirror can reduce the probability of this kind of traffic accident. In this paper, the behavior is explored and studied based on machine vision and image processing technology, and the related detection methods and technical schemes are proposed, which are verified by a large number of experiments and examples. Finally, a driver's rearview mirror viewing behavior detection system is developed. The main work and research results include: (1) on the basis of a large number of relevant technologies and literature at home and abroad, aiming at the problems that may be encountered in the subject, In this paper, a method for detecting the viewing behavior of drivers with rearview mirror is proposed, which only takes the outline of driver's face and neck as the target. The algorithm has the advantages of small task quantity, good real-time performance and high robustness. (2) based on the behavior characteristics of the driver, a static recognition and location algorithm for the driver's face and neck region is proposed, which is used to identify and locate the driver's face and neck area when the vehicle starts. The gray mean learning and static search and recognition of the driver's face neck skin under the current light source condition are completed. Then, a dynamic recognition and location algorithm for driver's face and neck region is proposed, which can be used to complete the learning of the gray mean value of the driver's face neck skin and the fast tracking and recognition of the face neck area when the vehicle is driving. Finally, the visible skin outline of the driver's face and neck is extracted and the characteristic parameters of the left and right area ratio are defined according to the vertical line of the neck base point. The image processing results show that the algorithm has good adaptive learning ability and anti-interference ability. (3) according to the difference of driver's face type, the installation position of camera, and the driver's hairstyle, The interference of wearing objects and so on leads to the difference of reference characteristic parameters. Combined with the analysis of driving eye movement gaze data, this paper reveals the local peak law of cumulative probability of characteristic parameters, and puts forward a threshold determination principle of rearview mirror viewing behavior. When the rearview mirror observation behavior is confirmed, all the parameter values in the process of viewing are used to update the cumulative probability and reestimate the parameters. The experimental data show that the cumulative probability of effective rearview mirror viewing data update can be adjusted adaptively. (4) the detection system is small in size and easy to popularize. On the platform of raspberry send 3 generation microprocessor and embedded Linux system, the user interface design uses Qt, image interface function to use image processing open source library OpenCV.. The test results show that the system has good real-time and universal ability.
【学位授予单位】:厦门理工学院
【学位级别】:硕士
【学位授予年份】:2016
【分类号】:U463.6;U495;TP391.41
[Abstract]:The statistical data show that 25% of the traffic accidents are directly related to the alert state of the driver, in which the turning of the vehicle, parallel lane, lane change and other steering and control processes are one of the main situations of traffic accidents. It is especially common that the driver does not pay attention to the traffic information behind the steering side of the vehicle. The real-time detection and necessary reminder of driver's rearview mirror can reduce the probability of this kind of traffic accident. In this paper, the behavior is explored and studied based on machine vision and image processing technology, and the related detection methods and technical schemes are proposed, which are verified by a large number of experiments and examples. Finally, a driver's rearview mirror viewing behavior detection system is developed. The main work and research results include: (1) on the basis of a large number of relevant technologies and literature at home and abroad, aiming at the problems that may be encountered in the subject, In this paper, a method for detecting the viewing behavior of drivers with rearview mirror is proposed, which only takes the outline of driver's face and neck as the target. The algorithm has the advantages of small task quantity, good real-time performance and high robustness. (2) based on the behavior characteristics of the driver, a static recognition and location algorithm for the driver's face and neck region is proposed, which is used to identify and locate the driver's face and neck area when the vehicle starts. The gray mean learning and static search and recognition of the driver's face neck skin under the current light source condition are completed. Then, a dynamic recognition and location algorithm for driver's face and neck region is proposed, which can be used to complete the learning of the gray mean value of the driver's face neck skin and the fast tracking and recognition of the face neck area when the vehicle is driving. Finally, the visible skin outline of the driver's face and neck is extracted and the characteristic parameters of the left and right area ratio are defined according to the vertical line of the neck base point. The image processing results show that the algorithm has good adaptive learning ability and anti-interference ability. (3) according to the difference of driver's face type, the installation position of camera, and the driver's hairstyle, The interference of wearing objects and so on leads to the difference of reference characteristic parameters. Combined with the analysis of driving eye movement gaze data, this paper reveals the local peak law of cumulative probability of characteristic parameters, and puts forward a threshold determination principle of rearview mirror viewing behavior. When the rearview mirror observation behavior is confirmed, all the parameter values in the process of viewing are used to update the cumulative probability and reestimate the parameters. The experimental data show that the cumulative probability of effective rearview mirror viewing data update can be adjusted adaptively. (4) the detection system is small in size and easy to popularize. On the platform of raspberry send 3 generation microprocessor and embedded Linux system, the user interface design uses Qt, image interface function to use image processing open source library OpenCV.. The test results show that the system has good real-time and universal ability.
【学位授予单位】:厦门理工学院
【学位级别】:硕士
【学位授予年份】:2016
【分类号】:U463.6;U495;TP391.41
【参考文献】
相关期刊论文 前10条
1 张波;王文军;成波;;基于人脸3D模型的驾驶人头部姿态检测[J];汽车工程;2016年01期
2 胡平;周文洪;;基于帧间差分和边缘差分的遗留物检测算法[J];计算机系统应用;2015年03期
3 付先平;王亚飞;袁国良;管潇;PELI Eli;罗罡;;基于粒子滤波的驾驶员视线自动校准算法[J];计算机学报;2015年12期
4 李勇达;张超;孟令君;;基于头部姿态特征的列车司机疲劳驾驶检测系统研究[J];交通信息与安全;2014年05期
5 李文胜;;基于树莓派的嵌入式Linux开发教学探索[J];电子技术与软件工程;2014年09期
6 李荣;刘坤;高文鹏;;基于视觉的目标姿态估计算法[J];黑龙江科技大学学报;2014年01期
7 张万枝;王增才;徐俊凯;;基于面部特征三角形的机车驾驶员头部姿态参数估计[J];铁道学报;2013年11期
8 邹奇敏;辛乐;陈阳舟;;基于3D人脸模型的驾驶员头部姿态鲁棒跟踪算法[J];计算机测量与控制;2011年12期
9 陈振学;常发亮;刘春生;徐建光;;基于Adaboost算法和人脸特征三角形的姿态参数估计[J];武汉大学学报(信息科学版);2011年10期
10 初秀民;万剑;严新平;毛U,
本文编号:2485642
本文链接:https://www.wllwen.com/kejilunwen/ruanjiangongchenglunwen/2485642.html