基于多机联合调用提高道路监控效率的方法

发布时间：2018-07-24 19:04

【摘要】：近年来,随着中国智能交通系统的发展,视频监控系统成为该领域研究的热点问题之一。然而随着人民生活水平的提高,城市道路交通压力越来越大,智能交通系统中监控摄像机的数量越来越多,但是城市视频摄像机监控效率却不见提高。本文通过改变多摄像机之间的联合调用,可以使摄像机获得视场最大化和图像信息最大化,从而提高城市道路的监控效率。在多摄像机与城市道路相结合部分,通过了解球形摄像机原理,可以帮助确定摄像机的监控范围;通过各种城市道路类型进行近似等效,可以更加容易的确定摄像机数量和位置。在多摄像机于城市道路中的运动轨迹设计部分,提出了整体设计方案,主要包括针对多摄像机联合调制建立数学模型-矩阵模型,近似模型元素于矩阵模型一一对应,矩阵模型中的工作状态划分,最终确定每个摄像机对应监控区域与运动轨迹。在界面的测试部分,通过数据库将各类车辆信息统计并存储,分别对正常工作状态和重点监控工作状态车辆数据处理,可以看出,正常监控工作状态监控效率达到88.08%,重点监控工作状态监控效率达到90.77%。最后,通过对重点监控工作状态数据中摄像机重点监控区域与非重点监控区域对比,结果证明:重点监控工作状态可以提高重点监控区域的监控效率,摄像机重点监控区域监控效率的提高是以非重点监控区域监控效率降低为代价,代价系数大小由道路类型和摄像机数量确定。
[Abstract]:In recent years, with the development of intelligent transportation system in China, video surveillance system has become one of the hot issues in this field. However, with the improvement of people's living standards, urban road traffic pressure is increasing, and the number of surveillance cameras in its is increasing, but the efficiency of urban video camera surveillance has not been improved. In this paper, by changing the joint call between multiple cameras, the camera can obtain the maximum view field and the maximum image information, so as to improve the efficiency of urban road monitoring. In the combination of multiple cameras and urban roads, by understanding the principle of spherical cameras, we can help to determine the monitoring range of cameras, and approximate equivalence through various types of urban roads. It is easier to determine the number and location of cameras. In the part of motion trajectory design of multi-camera in urban road, the overall design scheme is proposed, which mainly includes the establishment of mathematical model-matrix model for multi-camera joint modulation, and the approximate model elements corresponding to matrix model one-to-one. The working state of the matrix model is divided to determine the corresponding monitoring area and motion track of each camera. In the testing part of the interface, all kinds of vehicle information are counted and stored through the database, and the vehicle data processing in the normal working state and the key monitoring working state can be seen. The efficiency of normal monitoring and working state monitoring is 88.08, and the monitoring efficiency of key monitoring work state is 90.77. Finally, by comparing the key monitoring area with the non-key monitoring area in the key monitoring work state data, the results show that the key monitoring work state can improve the monitoring efficiency of the key monitoring area. The improvement of the surveillance efficiency of the camera monitoring area is at the cost of the decrease of the monitoring efficiency in the non-key monitoring area. The cost coefficient is determined by the road type and the number of cameras.
【学位授予单位】：南京大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN948.6

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