摘要
PTZ (Pan/Tilt/Zoom,云台全方位移动及镜头变倍、变焦控制)摄像机,也简称云台控制摄像机,由于可变焦、全景覆盖、可远程控制和自动跟踪等特点,在工程、交通和自然资源等行业应用广泛。但摄像机云台提供的角度和缩放等参数精度较低,且易受风雨等外界环境因素影响,因此高精度几何定位对PTZ摄像机而言依然是极大的挑战。本文利用杆塔PTZ摄像机以及大视野监测场景的特点,提出一种多源空间数据辅助的几何定位方法。(1)以高分七号立体影像和资源三号线阵影像生成的数字正射影像(DOM)和数字表面模型(DSM)作为控制数据来源,对PTZ摄像机拍摄的不同方位样本影像选刺控制点和位姿解算。(2)对于待计算影像,利用词汇树在样本数据库中检索最邻近影像。随后进行特征点匹配,并利用匹配得到特征点以及控制点,解算出该影像拍摄时刻的位置姿态参数。(3)利用解算的影像位姿,结合DSM求交,迭代计算对目标点的精确三维坐标。方法在小范围内的测试数据上表现出较高的定位精度,能够替代传统方法的外业控制点采集工作,降低工作难度,具备可靠性和可扩展性,可在自然资源、安全应急、生态环境等领域的监测场景中应用。
PTZ(Pan/Tilt/Zoom,omni-directional movement and lens doubling,zoom control)cameras,also referred to as PTZ control cameras,are widely used in industries such as engineering,transport and natural resources due to their zoomability,panoramic coverage,remote controlla-bility and automatic tracking.However,parameters such as angle and zoom provided by the camera head have low accuracy and are susceptible to external environmental factors such as wind and rain,so high-precision geometric positioning is still a great challenge for PTZ cameras.In this paper,we used the characteristics of PTZ camera of the pole tower as well as the large field of view monitoring scene to propose a multi-source spatial data-assisted geometric positioning method.①We took the digital orthophoto map(DOM)and digital surface model(DSM)generated from GF-7 stereo images and ZY-3 line array images as the source of control data,and selected the control points to solve the positional attitude for the sample images with different orientations taken by the PTZ camera.②For the images to be computed,we retrieved the nearest neighbor images in the sample database using a vocabulary tree.Subsequently,we performed feature point matching,and used the feature points as well as the control points obtained from the matching to solve the positional attitude parameters at the moment when the image was captured.③Using the solved image position pose,combined with ray-DSM intersection,we iteratively calculated the precise 3D coordinates of target point.The method shows high localization accuracy on a small range of test data,replaces the external control point acquisition of traditional methods,re-duces the work difficulty,has reliability and scalability,and can be applied in monitoring scenarios in natural resources,security and emergency response,ecological environment and other fields.
作者
孟小亮
胡予萱
王明霞
周志宇
刘昆波
王腾
高广
MENG Xiaoliang;HU Yuxuan;WANG Mingxia;ZHOU Zhiyu;LIU Kunbo;WANG Teng;GAO Guang(School of Remote Sensing Information Engineering,Wuhan University,Wuhan 430079,China;School of Artificial Intelligence,Jianghan University,Wuhan 430056,China;Surveying and Mapping Institute Lands and Resource Department of Guangdong Province,Guangzhou 510663,China;PopSmart Technology Co.,Ltd.,Ningbo 315042,China)
出处
《地理空间信息》
2024年第2期1-7,共7页
Geospatial Information
基金
国家自然科学基金资助项目(41971352)
宁波市重点研发计划项目(2023Z129)。
关键词
PTZ摄像机
几何定位
多源空间数据
词汇树
特征点匹配
PTZ camera
geometric localization
multi-source spatial data
vocabulary tree
feature point matching
