面向智能交通的单目视觉测距方法研究

与前方车辆距离是影响行车安全的重要因素,因此本文提出一种面向未来智能交通的前方车辆单目视觉测距方法.首先,提出融合物联网、智能识别、云计算技术的车联网模型,车辆可实时向车联网回传位置信息及前车图像,请求附近交通标志及前方车辆几何尺度信息,车辆端可计算图像坐标系下车道标志线、交通标志、车辆尺度信息.然后,建立单目相机数学模型,介绍以交通标志、车道分界线为合作标志的单目视觉测距方法.最后,综合应用单目视觉测距方法,设计了前方车辆自适应视觉测距方案.通过仿真实验,证明了单目视觉测距方法的正确性与有效性,可丰富驾驶辅助系统的前方车辆测距手段.     

传统方法在水下相机标定应用中的研究

针对加装保护壳体的水下相机光路较空气中复杂,传统成像模型及标定在水下是否满足工程要求的问题,在带畸变的小孔成像模型中利用传统方法进行了大气和水下的相机标定,验证了两种情况下标定偏差的存在;利用神经网络方法对水下相机标定进行了对比实验,结果显示传统方法在工程应用中的水下相机标定中仍具有优势。     

Monitoring wildlife crossing structures along highways in Changbai Mountain,China

In China, the construction and monitoring of wildlife crossing structures is uncommon. Mountainous area occupies two-thirds area of China. A lot of tunnels (similar to overpasses in developed countries), bridges, and culverts (similar to underpasses) are constructed along highways. In general, these structures are multifunctional, including wildlife migration. However, studies on monitoring these potential crossing structures are almost vacant. Taking two highways in Changbai Mountain area as case studies, infra-red camera trapping and snow tracking were used to investigate the efficiency of tunnels, bridges and culverts on the highways. A total of 13 medium and large-sized wildlife species crossed highway through tunnels, bridges and culverts. One third of species were Chinese national protective species, and almost all species were present within 500 m from Ring Changbai Mountain Scenic highway used bridges and culverts to cross this highway. The tunnel along the expressway (length = 1000 m) and the bridges along the highway (width > 8 m) have been important passages for ungulates, Eurasian red squirrels (Sciurus vulgaris), yellow throated martens (Martes flavigula) and sables (Martes zibellina). Different species preferred to different types of structures, although most species preferred to bridges and tunnels. We suggest that short fences should be set around the bridges and culverts to guide animals to cross the passages, especially for ungulates. Monitoring programs of uses of crossing structures by wildlife should be conducted for at least 2 months to catch most species activity.     

Contrasting the direct use of data from traffic radars and video-cameras with traffic simulation in the estimation of road emissions and PM hotspot analysis

This study investigates the effect of traffic volume and speed data on the simulation of vehicle emissions and hotspot analysis. Data from a microwave radar and video cameras were first used directly for emission modelling. They were then used as input to a traffic simulation model whereby vehicle drive cycles were extracted to estimate emissions. To reach this objective, hourly traffic data were collected from three periods including morning peak (6–9 am), midday (11–2 pm), and afternoon peak (3–6 pm) on a weekday (June 23, 2016) along a high-volume corridor in Toronto, Canada. Traffic volumes were detected by a single radar and two video cameras operated by the Southern Ontario Centre for Atmospheric Aerosol Research. Traffic volume and composition derived from the radar had lower accuracy than the video camera data and the radar performance varied by lane exhibiting poorer performance in the remote lanes. Radar speeds collected at a single point on the corridor had higher variability than simulated traffic speeds, and average speeds were closer after model calibration. Traffic emissions of nitrogen oxides (NOx) and particulate matter (PM₁₀ and PM_2.5) were estimated using radar data as well as using simulated traffic based on various speed aggregation methods. Our results illustrate the range of emission estimates (NO_x: 4.0–27.0 g; PM₁₀: 0.3–4.8 g; PM_2.5: 0.2–1.3 g) for the corridor. The estimates based on radar speeds were at least three times lower than emissions derived from simulated vehicle trajectories. Finally, the PM₁₀ and PM_2.5 near-road concentrations derived from emissions based on simulated speeds were two or three times higher than concentrations based on emissions derived using radar data. Our findings are relevant for project-level emission inventories and PM hot-spot analysis; caution must be exercised when using raw radar data for emission modeling purposes.     

Mobile Robot Hierarchical Simultaneous Localization and Mapping Using Monocular Vision

A hierarchical mobile robot simultaneous localization and mapping (SLAM) method that allows us to obtain accurate maps was presented. The local map level is composed of a set of local metric feature maps that are guaranteed to be statistically independent. The global level is a topological graph whose arcs are labeled with the relative location between local maps. An estimation of these relative locations is maintained with local map alignment algorithm, and more accurate estimation is calculated through a global minimization procedure using the loop closure constraint. The local map is built with Rao-Blackwellised particle filter (RBPF), where the particle filter is used to extending the path posterior by sampling new poses. The landmark position estimation and update is implemented through extended Kalman filter (EKF). Monocular vision mounted on the robot tracks the 3D natural point landmarks, which are structured with matching scale invariant feature transform (SIFT) feature pairs. The matching for multi-dimension SIFT features is implemented with a KD-tree in the time cost of O(lbN). Experiment results on Pioneer mobile robot in a real indoor environment show the superior performance of our proposed method.     

高速公路监控摄像机太阳能供电方案设计研究

针对高速公路监控摄像机远程供电困难的问题,结合环保、节能的原则,设计了监控摄像机太阳能供电系统,详细介绍太阳能供电设计方案,并进行了实例计算,最后对本文进行了总结。     

基于视频的城市快速路车辆异常行为检测

文章提出虚拟传感器的概念,针对城市快速路视频监控系统,改革单一功能摄像机,使其成为具人工智能的新型视频传感器,完成道路车辆跟踪及异常行为检测。异常检测算法运用带有时间和空间信息的车辆轨迹对自组织神经网络进行训练,获得神经网络参数后利用概率模型对实时车辆轨迹进行异常提取。该文所提算法能在嵌入式DM642视频处理平台上有效运行,能够提取诸如超低(高)速行驶、违章停车、违规掉头等异常行为,具有低运算量及较好的鲁棒性。     

视频监控系统摄像机技术发展趋势研究

郑州地铁5号线、市民文化服务区地下交通市政工程及后续线路单站摄像机数量均在90路以上,部分站点甚至超过110路。摄像机数量的增加为前期工程建设及后期运营维护带来了诸多挑战,如何在满足安防需求的前提下简化摄像机点位布放数量,提升运维效率成为一大课题。目前市场上全景摄像机种类较多,各摄像机厂家提供的产品性能参数、适用场景也不尽相同,本研究探讨视频监控系统现状及全景摄像机的应用。     

基于高分辨率摄像机的机动车违法检测系统

在目前应用的机动车视频违法检测系统中,广泛采用的是多摄像机分别拍摄违法行为全景及违法车辆车牌特写的技术方案。针对其存在证据性弱、系统调试复杂等缺点,设计并实现了一种基于高分辨率摄像机的视频违法检测系统,重点阐述了系统设计方案、软件结构、实现方法和实验结果。     

基于CCD传感器的缓冲器自由高度自动检测仪

介绍了利用二位图像处理方法对缓冲器进行实时处理的自由高度自动检测仪,硬件采用单片机和PLD就可以实现,大大降低了系统的成本。系统可以自动检测、调整CCD的感受光强,保证系统获取有效的图像信号。采用双标准试件自整定长度的输出—输入特性,保证了系统的测量精度。系统采用了筛选计量采样图像的方法,排除了测量基准参考点选择不当的测量误差。