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基于平行面多靶标标定的单目大视场平面测量

发布时间:2018-07-17 05:16
【摘要】:针对单目大视场平面测量时,测量平面内不便布置靶标和大尺寸靶标难以制作的问题,提出一种利用布设在平行面上的小尺寸平面靶标进行标定的方法。选定一个平行面为标定平面,将单个小尺寸平面靶标合理放置在标定平面的多个位置拍摄,整合构造出一个大尺寸平面靶标,采用非线性优化的方法进行摄像机内、外参的优化求解。结合平行约束和距离参数得到测量平面与图像平面的单应矩阵,实现大视场平面测量。建立平面测量的精度模型,对测量区域各处精度的分布以及影响测量精度的摄像机内参、安装角度和高度等因素进行理论分析和实验验证。实验结果表明:该方法可有效保证整体测量精度;在上底920mm、下底1360mm、高920mm的梯形视场内标定,距标定平面200mm的测量平面内的测量误差低于0.6%;测量区域内各处误差的分布趋势与精度模型一致。此方法完全适用于大视场平面测量。
[Abstract]:In order to solve the problem that it is difficult to make the target and the large size target in the measurement plane, a calibration method is proposed by using the small size target placed on the parallel surface. A parallel plane is chosen as the calibration plane, and a single small plane target is reasonably placed in several locations of the calibration plane for shooting, and a large size plane target is integrated and constructed, and the nonlinear optimization method is used to carry out the camera. Optimization of external parameters. Combining parallel constraints and distance parameters, the monoclinic matrix of the measurement plane and the image plane is obtained, and the large field of view plane measurement is realized. The precision model of plane measurement is established. The theoretical analysis and experimental verification are carried out on the distribution of accuracy in different parts of the measurement area and the factors affecting the measurement accuracy, such as camera internal parameters, installation angle and height, and so on. The experimental results show that this method can effectively guarantee the overall measurement accuracy, and calibrate in the trapezoidal field of view with the upper bottom 920mm, the lower bottom 1360mm and the high 920mm field of view. The measurement error in the measurement plane of 200mm from the calibrated plane is less than 0.6, and the distribution trend of the errors in the measurement area is consistent with the precision model. This method is fully applicable to the measurement of large field of view plane.
【作者单位】: 北京航空航天大学机器人研究所;
【分类号】:TP391.41

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