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  • Ceres Solver Bibliography

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    Bibliography

    [Agarwal] S. Agarwal, N. Snavely, S. M. Seitz and R. Szeliski, Bundle Adjustment in the LargeProceedings of the European Conference on Computer Vision, pp. 29–42, 2010.
    [Bjorck] A. Bjorck, Numerical Methods for Least Squares Problems, SIAM, 1996
    [Brown] D. C. Brown, A solution to the general problem of multiple station analytical stereo triangulation, Technical Report 43, Patrick Airforce Base, Florida, 1958.
    [ByrdNocedal] R. H. Byrd, J. Nocedal, R. B. Schanbel, Representations of Quasi-Newton Matrices and their use in Limited Memory MethodsMathematical Programming 63(4):129–-156, 1994.
    [ByrdSchnabel] R.H. Byrd, R.B. Schnabel, and G.A. Shultz, Approximate solution of the trust region problem by minimization over two dimensional subspacesMathematical programming, 40(1):247–263, 1988.
    [Chen] Y. Chen, T. A. Davis, W. W. Hager, and S. Rajamanickam, Algorithm 887: CHOLMOD, Supernodal Sparse Cholesky Factorization and Update/DowndateTOMS, 35(3), 2008.
    [Conn] A.R. Conn, N.I.M. Gould, and P.L. Toint, Trust region methodsSociety for Industrial Mathematics, 2000.
    [GolubPereyra] G.H. Golub and V. Pereyra, The differentiation of pseudo-inverses and nonlinear least squares problems whose variables separateSIAM Journal on numerical analysis, 10(2):413–432, 1973.
    [HartleyZisserman] R.I. Hartley & A. Zisserman, Multiview Geometry in Computer Vision, Cambridge University Press, 2004.
    [KanataniMorris] K. Kanatani and D. D. Morris, Gauges and gauge transformations for uncertainty description of geometric structure with indeterminacyIEEE Transactions on Information Theory 47(5):2017-2028, 2001.
    [Keys] R. G. Keys, Cubic convolution interpolation for digital image processingIEEE Trans. on Acoustics, Speech, and Signal Processing, 29(6), 1981.
    [KushalAgarwal] A. Kushal and S. Agarwal, Visibility based preconditioning for bundle adjustmentIn Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2012.
    [Kanzow] C. Kanzow, N. Yamashita and M. Fukushima, Levenberg–Marquardt methods with strong local convergence properties for solving nonlinear equations with convex constraintsJournal of Computational and Applied Mathematics, 177(2):375–397, 2005.
    [Levenberg] K. Levenberg, A method for the solution of certain nonlinear problems in least squaresQuart. Appl. Math, 2(2):164–168, 1944.
    [LiSaad] Na Li and Y. Saad, MIQR: A multilevel incomplete qr preconditioner for large sparse least squares problemsSIAM Journal on Matrix Analysis and Applications, 28(2):524–550, 2007.
    [Madsen] K. Madsen, H.B. Nielsen, and O. Tingleff, Methods for nonlinear least squares problems, 2004.
    [Mandel] J. Mandel, On block diagonal and Schur complement preconditioningNumer. Math., 58(1):79–93, 1990.
    [Marquardt] D.W. Marquardt, An algorithm for least squares estimation of nonlinear parametersJ. SIAM, 11(2):431–441, 1963.
    [Mathew] T.P.A. Mathew, Domain decomposition methods for the numerical solution of partial differential equations, Springer Verlag, 2008.
    [NashSofer] S.G. Nash and A. Sofer, Assessing a search direction within a truncated newton methodOperations Research Letters, 9(4):219–221, 1990.
    [Nocedal] J. Nocedal, Updating Quasi-Newton Matrices with Limited StorageMathematics of Computation, 35(151): 773–782, 1980.
    [NocedalWright] J. Nocedal & S. Wright, Numerical Optimization, Springer, 2004.
    [Oren] S. S. Oren, Self-scaling Variable Metric (SSVM) Algorithms Part II: Implementation and Experiments, Management Science, 20(5), 863-874, 1974.
    [Press] W. H. Press, S. A. Teukolsky, W. T. Vetterling & B. P. Flannery, Numerical Recipes, Cambridge University Press, 2007.
    [Ridders] C. J. F. Ridders, Accurate computation of F’(x) and F’(x) F”(x), Advances in Engineering Software 4(2), 75-76, 1978.
    [RuheWedin] A. Ruhe and P.Å. Wedin, Algorithms for separable nonlinear least squares problems, Siam Review, 22(3):318–337, 1980.
    [Saad] Y. Saad, Iterative methods for sparse linear systems, SIAM, 2003.
    [Stigler] S. M. Stigler, Gauss and the invention of least squaresThe Annals of Statistics, 9(3):465-474, 1981.
    [TenenbaumDirector] J. Tenenbaum & B. Director, How Gauss Determined the Orbit of Ceres.
    [TrefethenBau] L.N. Trefethen and D. Bau, Numerical Linear Algebra, SIAM, 1997.
    [Triggs] B. Triggs, P. F. Mclauchlan, R. I. Hartley & A. W. Fitzgibbon, Bundle Adjustment: A Modern Synthesis, Proceedings of the International Workshop on Vision Algorithms: Theory and Practice, pp. 298-372, 1999.
    [Wiberg] T. Wiberg, Computation of principal components when data are missing, In Proc. Second Symp. Computational Statistics, pages 229–236, 1976.
    [WrightHolt] S. J. Wright and J. N. Holt, An Inexact Levenberg Marquardt Method for Large Sparse Nonlinear Least SquaresJournal of the Australian Mathematical Society Series B, 26(4):387–403, 1985.
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  • 原文地址:https://www.cnblogs.com/cx2016/p/12355825.html
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