面向工业摄影测量的一种混合式相对定向算法
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摘要
针对工业摄影测量中多基线、大倾角交向摄影时相对定向困难的问题,提出一种混合式相对定向算法。算法先利用本质矩阵分解确立相对定向参数初值,再利用非线性优化计算精确解。从共面条件获得的行列式出发,推导本质矩阵与相对定向参数的内在联系,给出求解本质矩阵的两种方法。然后讨论本质矩阵奇异值分解计算旋转矩阵和平移矢量,同时给出剔除伪解的依据。基于共面条件方程,建立相对定向参数非线性优化的目标函数。定向精度对比试验验证了所提出的混合算法的稳定性和高精度,对卫星天线曲面的测量试验也进一步说明该算法在工程实践中的适用性和可靠性。
In order to satisfy the multiple-baselines and large-dip-angles photogrammetry applied in industry, a hybrid algorithm of relative orientation is presented. In this algorithm, the initial parameters of the relative orientation are established by the decomposition of the essential matrix, and then the exact solution of the parameters are calculated by a nonlinear optimization. First, the relationship between the essential matrix and the orientation parameters is derived by the determinant from the coplanarity condition, with two solving methods of the essential matrix being introduced, and then the rotation matrix and translation vector between two images are calculated by singular value decomposition(SVD) of the essential matrix, including the removal of the pseudo solutions. Second, according to the coplanarity condition equation, the cost function of relative orientation parameters for non-linear optimization is build. Finally, the result in comparison experiment indicates that the hybrid algorithm has acquired better stabilization and high precision, and the application in measuring curved surface of the antenna also identifies its practicability and reliability.
In order to satisfy the multiple-baselines and large-dip-angles photogrammetry applied in industry, a hybrid algorithm of relative orientation is presented. In this algorithm, the initial parameters of the relative orientation are established by the decomposition of the essential matrix, and then the exact solution of the parameters are calculated by a nonlinear optimization. First, the relationship between the essential matrix and the orientation parameters is derived by the determinant from the coplanarity condition, with two solving methods of the essential matrix being introduced, and then the rotation matrix and translation vector between two images are calculated by singular value decomposition(SVD) of the essential matrix, including the removal of the pseudo solutions. Second, according to the coplanarity condition equation, the cost function of relative orientation parameters for non-linear optimization is build. Finally, the result in comparison experiment indicates that the hybrid algorithm has acquired better stabilization and high precision, and the application in measuring curved surface of the antenna also identifies its practicability and reliability.
引文
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[2] 李云雷,张曦,屠大维.形貌视觉测量中立体拼接靶标的设计及应用[J].仪器仪表学报,2017,38(09):2161—2169.Li Yunlei,Zhang Xi,Tu Dawei.Design and application of 3D target for stitching in shape vision measurement[J].Chinese Journal of Scientific and Instrument,2017,38(09):2161—2169.
[3] 黄鹏程,杨波,万新军,等.基于双目视觉的多点三维振动测量系统[J].光学技术,2018,44(04):448—452.Huang Pengcheng,Yang Bo,Wan Xinjun,et al.The measurement system of multi-point three-dimensional vibration based on binocular vision [J].Optical Technique,2018,44(04):448—452.
[4] 张凯,张好运,卢旭升,等.无人机海岛礁航空摄影测量技术应用[J].测绘通报,2018(09):87—90.Zhang Kai,Zhang Haoyun,Lu Xusheng,et al.Application of unmanned aerial vehicle aerial Photogrammetry in island[J].Bulletin of Surveying and Mapping,2018(09):87—90.
[5] 王君,董明利,李巍,等.大视场摄影测量相机的相对定向[J].光学技术,2018,44(05):549—554.Wang Jun,Dong Mingli,Li Wei,et al.Camera relative orientation in Large-scale photogrammetry[J].Optical Technique,2018,44(05):549—554.
[6] Luhmann T,Robson S,Kyle S,et al.Close range photogrammetry:principles,techniques and applications [M].Dunbeath:Whittles Publishing,2006.
[7] 陆珏,陈义,郑波.多基线近景摄影测量连续像对相对定向[J].同济大学学报:自然科学版,2010,38(3):442—447.Lu Jue,Cheng Yi,Zheng Bo.Research on dependent relative orientation in multi-baseline close-range photogrammetry[J].Journal of Tongji University:Natural Science,2010,38(3):442—447.
[8] 周拥军,邓才华.利用HGA和单位四元数的相对定向解法[J].武汉大学学报:信息科学版,2011,36(6):670—673.Zhou Yongjun,Deng Caihua.A new method for relative orientation with hybrid genetic algorithm and unit quaternion[J].Geomatics and Information Science of Wuhan University,2011,36(6):670—673.
[9] Mcglone J.C,Mikhail E.M,Bethel J.S.Manual of Photogrammetry[M].5th ed.Maryland:Asprs,2004.
[10] 于英,黄桂平,刑坤.双目立体视觉测量中相对定向的直接解法[J].红外与激光工程,2009,38(增刊):339—342.Yu Ying,Huang Guiping,Xing Kun.Direct closed-form solution to general relative orientation[J].Infrared and Laser Engineering,2009,38(Supplement):339—342.
[11] 李巍,董明利,孙鹏,等.大尺寸摄影测量局部参数优化相对定向方法[J].仪器仪表学报,2014,35(9):2053—2060.Li Wei,Dong Mingli,Sun Peng,et al.Relative orientation method for large-scale photogrammetry with local parameter optimization[J].Chinese Journal of Scientific and Instrument,2014,35(9):2053—2060.
[12] Hartley R,Zisserman A.Multiple view geometry in computer vision[M].2th ed.Cambridge:Cambridge University Press,2003.
[13] 马颂德,张正友.计算机视觉[M].北京:科学出版社,2003.Ma Songde,Zhang Zhengyou.Computer vision theory of computation and algorithm[M].Beijing:Science Press,2003.
[14] Zhang Zhengyou.A flexible new technique for camera calibration[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(11):1330—1334.
[15] Triggs B.Bundle adjustment-a modern synthesis[M] Vision Algorithms:Theory and Practice.Springer Berlin Heidelberg,1999.
[16] Madsen K,Nielsen H,Tingleff O.Methods for non-linear least squares problems[R] Lyngby,Copenhagen:Technical University of Denmark,2004.
[17] Lourakis M I A,Argyros A A.SBA[J].ACM Transactions on Mathematical Software,2009,36(1):1—30.