基于正交迭代的参考点不确定相机位姿估计
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摘要
相机的位姿估计广泛应用于计算机视觉和机器人学等领域。针对相机位姿估计的稳定性与实时性,基于正交迭代算法,提出了一种考虑空间参考点不确定性的相机位姿估计算法。该算法的关键思想是在考虑摄像头畸变的情况下,根据参考点的位置特征获得相应权值,并利用加速正交迭代思想对迭代过程中的重复计算进行规整,最小化加权重投影物方残差函数获得相机位姿。模拟数据实验和真实图像实验表明,该算法计算精度更高,速度更快,时间复杂度较低。在空间参考点深度较大或者偏离摄像头光轴的情况下,该算法的时间复杂度和精度均优于现有的正交迭代算法,从而实现了相机位姿估计的实时性。
Camera pose estimation is widely used in computer vision and robotics.Aiming at the stability and realtime performance of camera pose estimation,a camera pose estimation algorithm considering the uncertainty of spatial reference points based on orthogonal iterative algorithm is proposed.The key idea of the algorithm is to obtain the weights of the corresponding feature points in consideration of camera distortion and use an accelerated orthogonal iterative algorithm to regularize the repeated calculations in the iterative process.And the camera pose is obtained by minimizing the weighted re-projection object residual function.Results of simulation data experiments and real image experiment show that the proposed algorithm has higher calculation accuracy,faster speed,and lower time complexity.In the case of deep spatial feature points or the feature points deviating from the optical axis of the camera,the time complexity and accuracy of the algorithm are better than the existing orthogonal iterative algorithms,indicating its feasibility in the real-time estimation of camera pose.
Camera pose estimation is widely used in computer vision and robotics.Aiming at the stability and realtime performance of camera pose estimation,a camera pose estimation algorithm considering the uncertainty of spatial reference points based on orthogonal iterative algorithm is proposed.The key idea of the algorithm is to obtain the weights of the corresponding feature points in consideration of camera distortion and use an accelerated orthogonal iterative algorithm to regularize the repeated calculations in the iterative process.And the camera pose is obtained by minimizing the weighted re-projection object residual function.Results of simulation data experiments and real image experiment show that the proposed algorithm has higher calculation accuracy,faster speed,and lower time complexity.In the case of deep spatial feature points or the feature points deviating from the optical axis of the camera,the time complexity and accuracy of the algorithm are better than the existing orthogonal iterative algorithms,indicating its feasibility in the real-time estimation of camera pose.
引文
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[25]Lu C P,Hager G D,Mjolsness E.Fast and globally convergent pose estimation from video images[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(6):610-622.
[26]Li X,Long G C,Liu J B,et al.Accelerative orthogonal iteration algorithm for camera pose estimation[J].Acta Optica Sinica,2015,35(1):0115004.李鑫,龙古灿,刘进博,等.相机位姿估计的加速正交迭代算法[J].光学学报,2015,35(1):0115004.
[27]Zhou R,Zhang Z Y,Huang X H.Weighted orthogonal iteration algorithm for camera pose estimation[J].Acta Optica Sinica,2018,38(5):0515002.周润,张征宇,黄叙辉.相机位姿估计的加权正交迭代算法[J].光学学报,2018,38(5):0515002.
[28]Yue X K,Wu Y Y,Wu K Z.A novel binocular OI(orthogonal iteration)fusion algorithm better for estimation of spacecraft position and attitude[J].Journal of Northwestern Polytechnical University,2011,29(4):559-563.岳晓奎,武媛媛,吴侃之.基于视觉信息的航天器位姿估计迭代算法[J].西北工业大学学报,2011,29(4):559-563.
[2]Ke T,Roumeliotis S I.An efficient algebraic solution to the perspective-three-point problem[C]∥IEEEConference on Computer Vision and Pattern Recognition(CVPR),2017:4618-4626.
[3]Wu F L,Liu J J,Ren X,et al.Deep space exploration panoramic camera calibration technique based on circular markers[J].Acta Optica Sinica,2013,33(11):1115002.吴凡路,刘建军,任鑫,等.基于圆形标志点的深空探测全景相机标定方法[J].光学学报,2013,33(11):1115002.
[4]Tahri O,Chaumette F.Complex objects pose estimation based on image moment invariants[C]∥Proceedings of the 2005 IEEE International Conference on Robotics and Automation,2005:436-441.
[5]Azuma R,Baillot Y,Behringer R,et al.Recent advances in augmented reality[J].IEEE Computer Graphics and Applications,2001,21(6):34-47.
[6]Fischler M A,Bolles R C.Random sample consensus:a paradigm for model fitting with applications to image analysis and automated cartography[J].Communications of the ACM,1981,24(6):381-395.
[7]Quan L,Lan Z D.Linear N-point camera pose determination[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1999,21(8):774-780.
[8]Kneip L,Scaramuzza D,Siegwart R.A novel parametrization of the perspective-three-point problem for a direct computation of absolute camera position and orientation[C]∥IEEE Conference on Computer Vision and Pattern Recognition(CVPR),2011:2969-2976.
[9]Kukelova Z,Bujnak M,Pajdla T.Closed-form solutions to minimal absolute pose problems with known vertical direction[C]∥Asian Conference on Computer Vision,2010:216-229.
[10]Nistér D,Stewénius H.A minimal solution to the generalised 3-point pose problem[J].Journal of Mathematical Imaging and Vision,2007,27(1):67-79.
[11]Wang P,Sun C K,Zhang Z M.Linear pose estimation with a monocular vision system[J].Chinese Journal of Scientific Instrument,2011,32(5):1126-1131.王鹏,孙长库,张子淼.单目视觉位姿测量的线性求解[J].仪器仪表学报,2011,32(5):1126-1131.
[12]Wu F C,Hu Z Y.A study on the P5P problem[J].Journal of Software,2001,12(5):768-775.吴福朝,胡占义.关于P5P问题的研究[J].软件学报,2001,12(5):768-775.
[13]Li S Q,Xu C,Xie M.A robust O(n)solution to the perspective-n-point problem[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(7):1444-1450.
[14]Abdel-Aziz Y I,Karara H M,Hauck M.Direct linear transformation from comparator coordinates into object space coordinates in close-range photogrammetry[J].Photogrammetric Engineering&Remote Sensing,2015,81(2):103-107.
[15]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):155-166.
[16]Hesch J A,Roumeliotis S I.A direct least-squares(DLS)method for PnP[C]∥International Conference on Computer Vision,2011:383-390.
[17]Zheng Y Q,Kuang Y B,Sugimoto S,et al.Revisiting the PnP problem:a fast,general and optimal solution[C]∥IEEE International Conference on Computer Vision,2013:2344-2351.
[18]Ferraz L,Binefa X,Moreno-Noguer F.Very fast solution to the PnP problem with algebraic outlier rejection[C]∥IEEE Conference on Computer Vision and Pattern Recognition,2014:501-508.
[19]Yang S,Wu F C.Weighted linear methods for the camera pose estimation[J].Journal of Software,2011,22(10):2476-2487.杨森,吴福朝.摄像机位姿的加权线性算法[J].软件学报,2011,22(10):2476-2487.
[20]Wang P,Xu G L,Cheng Y H,et al.A simple,robust and fast method for the perspective-n-point problem[J].Pattern Recognition Letters,2018,108:31-37.
[21]Hartley R,Zisserman A.Multipleview geometry in computer vision[M].Cambridge:Cambridge University Press,2003:1865-1872.
[22]Dementhon D F,Davis L S.Model-based object pose in 25lines of code[J].International Journal of Computer Vision,1995,15(1/2):123-141.
[23]Lu C P,Hager G D,Mjolsness E.Fast and globally convergent pose estimation from video images[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(6):610-622.
[24]Haralick R M,Joo H,Lee C,et al.Pose estimation from corresponding point data[J].IEEE Transactions on Systems,Man,and Cybernetics,1989,19(6):1426-1446.
[25]Lu C P,Hager G D,Mjolsness E.Fast and globally convergent pose estimation from video images[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(6):610-622.
[26]Li X,Long G C,Liu J B,et al.Accelerative orthogonal iteration algorithm for camera pose estimation[J].Acta Optica Sinica,2015,35(1):0115004.李鑫,龙古灿,刘进博,等.相机位姿估计的加速正交迭代算法[J].光学学报,2015,35(1):0115004.
[27]Zhou R,Zhang Z Y,Huang X H.Weighted orthogonal iteration algorithm for camera pose estimation[J].Acta Optica Sinica,2018,38(5):0515002.周润,张征宇,黄叙辉.相机位姿估计的加权正交迭代算法[J].光学学报,2018,38(5):0515002.
[28]Yue X K,Wu Y Y,Wu K Z.A novel binocular OI(orthogonal iteration)fusion algorithm better for estimation of spacecraft position and attitude[J].Journal of Northwestern Polytechnical University,2011,29(4):559-563.岳晓奎,武媛媛,吴侃之.基于视觉信息的航天器位姿估计迭代算法[J].西北工业大学学报,2011,29(4):559-563.