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- .. _sec-bibliography:
- ============
- Bibliography
- ============
- Background Reading
- ==================
- For a short but informative introduction to the subject we recommend
- the booklet by [Madsen]_ . For a general introduction to non-linear
- optimization we recommend [NocedalWright]_. [Bjorck]_ remains the
- seminal reference on least squares problems. [TrefethenBau]_ is our
- favorite text on introductory numerical linear algebra. [Triggs]_
- provides a thorough coverage of the bundle adjustment problem.
- References
- ==========
- .. [Agarwal] S. Agarwal, N. Snavely, S. M. Seitz and R. Szeliski,
- **Bundle Adjustment in the Large**, *Proceedings 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 Methods**, *Mathematical 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 subspaces**, *Mathematical 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/Downdate**, *TOMS*, 35(3), 2008.
- .. [Conn] A.R. Conn, N.I.M. Gould, and P.L. Toint, **Trust region
- methods**, *Society for Industrial Mathematics*, 2000.
- .. [Dellaert] F. Dellaert, J. Carlson, V. Ila, K. Ni and C. E. Thorpe,
- **Subgraph-preconditioned conjugate gradients for large scale SLAM**,
- *International Conference on Intelligent Robots and Systems*, 2010.
- .. [GolubPereyra] G.H. Golub and V. Pereyra, **The differentiation of
- pseudo-inverses and nonlinear least squares problems whose
- variables separate**, *SIAM Journal on numerical analysis*,
- 10(2):413-432, 1973.
- .. [GouldScott] N. Gould and J. Scott, **The State-of-the-Art of
- Preconditioners for Sparse Linear Least-Squares Problems**,
- *ACM Trans. Math. Softw.*, 43(4), 2017.
- .. [HartleyZisserman] R.I. Hartley & A. Zisserman, **Multiview
- Geometry in Computer Vision**, Cambridge University Press, 2004.
- .. [Hertzberg] C. Hertzberg, R. Wagner, U. Frese and L. Schroder,
- **Integrating Generic Sensor Fusion Algorithms with Sound State
- Representations through Encapsulation of Manifolds**, *Information
- Fusion*, 14(1):57-77, 2013.
- .. [KanataniMorris] K. Kanatani and D. D. Morris, **Gauges and gauge
- transformations for uncertainty description of geometric structure
- with indeterminacy**, *IEEE Transactions on Information Theory*
- 47(5):2017-2028, 2001.
- .. [Keys] R. G. Keys, **Cubic convolution interpolation for digital
- image processing**, *IEEE Trans. on Acoustics, Speech, and Signal
- Processing*, 29(6), 1981.
- .. [KushalAgarwal] A. Kushal and S. Agarwal, **Visibility based
- preconditioning for bundle adjustment**, *In 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
- constraints**, *Journal of Computational and Applied Mathematics*,
- 177(2):375-397, 2005.
- .. [Levenberg] K. Levenberg, **A method for the solution of certain
- nonlinear problems in least squares**, *Quart. Appl. Math*,
- 2(2):164-168, 1944.
- .. [LiSaad] Na Li and Y. Saad, **MIQR: A multilevel incomplete qr
- preconditioner for large sparse least squares problems**, *SIAM
- 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
- preconditioning**, *Numer. Math.*, 58(1):79-93, 1990.
- .. [Marquardt] D.W. Marquardt, **An algorithm for least squares
- estimation of nonlinear parameters**, *J. 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 method**, *Operations Research Letters*,
- 9(4):219-221, 1990.
- .. [Nocedal] J. Nocedal, **Updating Quasi-Newton Matrices with Limited
- Storage**, *Mathematics 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
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- .. [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.
- .. [Simon] I. Simon, N. Snavely and S. M. Seitz, **Scene Summarization
- for Online Image Collections**, *International Conference on Computer Vision*, 2007.
- .. [Stigler] S. M. Stigler, **Gauss and the invention of least
- squares**, *The 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
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