基于场景模型的双目相机动态检校方法
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摘要
提出了一种基于场景模型的双目相机内、外方位元素的动态检校方法.初始检校过程构建了场景全局三维模型并以此为基础分别初步解算内、外方位元素,然后进行联合优化;更新检校过程利用已建立的场景模型,恢复场景模型与影像的关联,再通过联合优化更新相机的检校参数.实际场景实验验证结果表明:该方法的检校完整度优于基于即时定位和地图构建(SLAM)的检校方法,精度优于传统棋盘格检校方法.
A scene model based stereo-camera calibration method is presented in this paper.The initial calibration process firstly constructs a global scene model,and based on this,both intrinsic and extrinsic parameters of the stereocamera are estimated separately and optimized jointly.The update calibration utilizes the established scene model to restore three dimention-two dimention relation between model coordinate and image coordinate,with the relation,stereocamera parameters are updated through joint optimization.The experiments in real-world show that the method calibrates all the parameters while SLAM-based method only solves a part,and the accuracy of the method is better than the chess-board based method.
A scene model based stereo-camera calibration method is presented in this paper.The initial calibration process firstly constructs a global scene model,and based on this,both intrinsic and extrinsic parameters of the stereocamera are estimated separately and optimized jointly.The update calibration utilizes the established scene model to restore three dimention-two dimention relation between model coordinate and image coordinate,with the relation,stereocamera parameters are updated through joint optimization.The experiments in real-world show that the method calibrates all the parameters while SLAM-based method only solves a part,and the accuracy of the method is better than the chess-board based method.
引文
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[2]刘昱岗,王卓君,王福景,等.基于双目立体视觉的倒车环境障碍物测量方法[J].交通运输系统工程与信息,2016,16(4):79.LIU Yugang, WANG Zhuojun, WANG Fujing,et al.Vehicle reversing obstacle measurement based on binocularcamera stereo vision[J].Journal of Transportation Systems Engineering and Information Technology,2016,16(4):79.
[3] ZHANG Z.Flexible camera calibration by viewing aplane from unknown orientations[C]//The Proceedings of the Seventh IEEE International Conference on Computer Vision.Kerkyra:IEEE,1999:666-673.
[4] GEIGER A,MOOSMANN F,CAR,et al.Automatic camera and range sensor calibration using a single shot[C]//International Conference on Robotics and Automation.Saint Paul:IEEE,2012:3936-3943.
[5] CARRERA G,ANGELI A,DAVISON A J.SLAM-based automatic extrinsic calibration of a multi-camera rig[C]//International Conference on Robotics and Automation.Shanghai:IEEE,2011:2652-2659.
[6]HENG L,FURGALE P,POLLEFEYS M.Leveraging image-based localization for infrastructure-based calibration of a multi-camera rig[J].Journal of Field Robotics,2015,32(5):775.
[7] HARTLEY R,ZISSERMAN A.Multiple view geometry in computer vision[M].Cambridge:Cambridge University Press,2003.
[8]HARTLEY R,TRUMPF J,DAI Y,et al.Rotation averaging[J].International Journal of Computer Vision,2013,103(3):267.
[9]MARKLEY F L,CHENG Y,CRASSIDIS J L,et al.Averaging quaternions[J].Journal of Guidance Control and Dynamics,2007,30(4):1193.
[10] SCHONBERGER J L,FRAHM J M.Structure-from-motion revisited[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas:IEEE,2016:4104-4113.
[11]李金岭,刘鹂,乔书波,等.关于三维直角坐标七参数转换模型求解的讨论[J].测绘科学,2010,35(4):76.LI Jinling,LIU Li,QIAO Shubo,et al.Discussion on the determination of transformation parameters of 3D Cartesian coordinates[J].Science of Surveying and Mapping,2010,35(4):76.
[12] GLVEZ-LPEZ D,TARDOS J D.Bags of binary words for fast place recognition in image sequences[J].IEEE Transactions on Robotics,2012,28(5):1188.
[13] LEPETIT V,MORENO-NOGUER F,FUA P.EPnP:an accurate O(n)solution to the PnP problem[J].International Journal of Computer Vision,2009,81(2):155.
[14] FISCHLER M A,BOLLES R C.Random sample consensus:aparadigm for model fitting with applications to image analysis and automated cartography[J].Communications of the ACM,1981,24(6):381.
[15]FUSIELLO A, TRUCCO E, VERRI A. A compact algorithm for rectification of stereo pairs[J].Machine Vision and Applications,2000,12(1):16.
[16] KREOI,EGVIC S.Improving the egomotion estimation by correcting the calibration bias[C]//Proceedings of the10th International Conference on Computer Vision Theory and Applications.Berlin:VISAPP,2015:347-356.