1 .. _sec-bibliography: 2 3 ============ 4 Bibliography 5 ============ 6 7 .. [Agarwal] S. Agarwal, N. Snavely, S. M. Seitz and R. Szeliski, 8 **Bundle Adjustment in the Large**, *Proceedings of the European 9 Conference on Computer Vision*, pp. 29--42, 2010. 10 11 .. [Bjorck] A. Bjorck, **Numerical Methods for Least Squares 12 Problems**, SIAM, 1996 13 14 .. [Brown] D. C. Brown, **A solution to the general problem of 15 multiple station analytical stereo triangulation**, Technical 16 Report 43, Patrick Airforce Base, Florida, 1958. 17 18 .. [ByrdNocedal] R. H. Byrd, J. Nocedal, R. B. Schanbel, 19 **Representations of Quasi-Newton Matrices and their use in Limited 20 Memory Methods**, *Mathematical Programming* 63(4):129-156, 1994. 21 22 .. [ByrdSchnabel] R.H. Byrd, R.B. Schnabel, and G.A. Shultz, **Approximate 23 solution of the trust region problem by minimization over 24 two dimensional subspaces**, *Mathematical programming*, 25 40(1):247263, 1988. 26 27 .. [Chen] Y. Chen, T. A. Davis, W. W. Hager, and 28 S. Rajamanickam, **Algorithm 887: CHOLMOD, Supernodal Sparse 29 Cholesky Factorization and Update/Downdate**, *TOMS*, 35(3), 2008. 30 31 .. [Conn] A.R. Conn, N.I.M. Gould, and P.L. Toint, **Trust region 32 methods**, *Society for Industrial Mathematics*, 2000. 33 34 .. [GolubPereyra] G.H. Golub and V. Pereyra, **The differentiation of 35 pseudo-inverses and nonlinear least squares problems whose 36 variables separate**, *SIAM Journal on numerical analysis*, 37 10(2):413432, 1973. 38 39 .. [HartleyZisserman] R.I. Hartley & A. Zisserman, **Multiview 40 Geometry in Computer Vision**, Cambridge University Press, 2004. 41 42 .. [KanataniMorris] K. Kanatani and D. D. Morris, **Gauges and gauge 43 transformations for uncertainty description of geometric structure 44 with indeterminacy**, *IEEE Transactions on Information Theory* 45 47(5):2017-2028, 2001. 46 47 .. [KushalAgarwal] A. Kushal and S. Agarwal, **Visibility based 48 preconditioning for bundle adjustment**, *In Proceedings of the 49 IEEE Conference on Computer Vision and Pattern Recognition*, 2012. 50 51 .. [Levenberg] K. Levenberg, **A method for the solution of certain 52 nonlinear problems in least squares**, *Quart. Appl. Math*, 53 2(2):164168, 1944. 54 55 .. [LiSaad] Na Li and Y. Saad, **MIQR: A multilevel incomplete qr 56 preconditioner for large sparse least squares problems**, *SIAM 57 Journal on Matrix Analysis and Applications*, 28(2):524550, 2007. 58 59 .. [Madsen] K. Madsen, H.B. Nielsen, and O. Tingleff, **Methods for 60 nonlinear least squares problems**, 2004. 61 62 .. [Mandel] J. Mandel, **On block diagonal and Schur complement 63 preconditioning**, *Numer. Math.*, 58(1):7993, 1990. 64 65 .. [Marquardt] D.W. Marquardt, **An algorithm for least squares 66 estimation of nonlinear parameters**, *J. SIAM*, 11(2):431441, 67 1963. 68 69 .. [Mathew] T.P.A. Mathew, **Domain decomposition methods for the 70 numerical solution of partial differential equations**, Springer 71 Verlag, 2008. 72 73 .. [NashSofer] S.G. Nash and A. Sofer, **Assessing a search direction 74 within a truncated newton method**, *Operations Research Letters*, 75 9(4):219221, 1990. 76 77 .. [Nocedal] J. Nocedal, **Updating Quasi-Newton Matrices with Limited 78 Storage**, *Mathematics of Computation*, 35(151): 773--782, 1980. 79 80 .. [NocedalWright] J. Nocedal & S. Wright, **Numerical Optimization**, 81 Springer, 2004. 82 83 .. [Oren] S. S. Oren, **Self-scaling Variable Metric (SSVM) Algorithms 84 Part II: Implementation and Experiments**, Management Science, 85 20(5), 863-874, 1974. 86 87 .. [RuheWedin] A. Ruhe and P.A. Wedin, **Algorithms for separable 88 nonlinear least squares problems**, Siam Review, 22(3):318337, 89 1980. 90 91 .. [Saad] Y. Saad, **Iterative methods for sparse linear 92 systems**, SIAM, 2003. 93 94 .. [Stigler] S. M. Stigler, **Gauss and the invention of least 95 squares**, *The Annals of Statistics*, 9(3):465-474, 1981. 96 97 .. [TenenbaumDirector] J. Tenenbaum & B. Director, **How Gauss 98 Determined the Orbit of Ceres**. 99 100 .. [TrefethenBau] L.N. Trefethen and D. Bau, **Numerical Linear 101 Algebra**, SIAM, 1997. 102 103 .. [Triggs] B. Triggs, P. F. Mclauchlan, R. I. Hartley & 104 A. W. Fitzgibbon, **Bundle Adjustment: A Modern Synthesis**, 105 Proceedings of the International Workshop on Vision Algorithms: 106 Theory and Practice, pp. 298-372, 1999. 107 108 .. [Wiberg] T. Wiberg, **Computation of principal components when data 109 are missing**, In Proc. *Second Symp. Computational Statistics*, 110 pages 229236, 1976. 111 112 .. [WrightHolt] S. J. Wright and J. N. Holt, **An Inexact 113 Levenberg Marquardt Method for Large Sparse Nonlinear Least 114 Squares**, *Journal of the Australian Mathematical Society Series 115 B*, 26(4):387403, 1985. 116 117 118 119 120