Bibliografia

AAK71

Y.I. Abdel-Aziz and H.M. Karara.
Direct linear transformation from comparator coordinates into object space coordinates in close-range photogrammetry.
In Proc. ASP/UI Symp. on Close-Range Photogrammetry, pages 1–18, Urbana, Illinois, January 1971.

AHB87

K. S. Arun, T. S. Huang, and S. D. Blostein.
Least-squares fitting of two 3-d point sets.
IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-9(5):698–700, 1987.

AL92

Wayne Iba Ai and Pat Langley.
Induction of one-level decision trees.
In Proceedings of the Ninth International Conference on Machine Learning, pages 233–240. Morgan Kaufmann, 1992.

B$^+$84

Leo Breiman et al.
Classification and Regression Trees.
Chapman & Hall, New York, 1984.

Bea78

P. R. Beaudet.
Rotationally invariant image operators.
In International Conference on Pattern Recognition, 1978.

BETVG08

Herbert Bay, Andreas Ess, Tinne Tuytelaars, and Luc Van Gool.
Speeded-up robust features (surf).
Comput. Vis. Image Underst., 110:346–359, June 2008.

Bis06

Christopher M. Bishop.
Pattern Recognition and Machine Learning (Information Science and Statistics).
Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2006.

BR96

Michael J Black and Anand Rangarajan.
On the unification of line processes, outlier rejection, and robust statistics with applications in early vision.
International Journal of Computer Vision, 19(1):57–91, 1996.

Bro66

Duane C Brown.
Decentering distortion of lenses.
Photogrammetric Engineering, 32(3):444–462, 1966.

Che03

Zhe Chen.
Bayesian Filtering: From Kalman Filters to Particle Filters, and Beyond.
Technical report, McMaster University, 2003.

CKY09

Sunglok Choi, Taemin Kim, and Wonpil Yu.
Performance evaluation of ransac family.
In Proceedings of the British Machine Vision Conference, pages 81.1–81.12. BMVA Press, 2009.
doi:10.5244/C.23.81.

CLSF10

Michael Calonder, Vincent Lepetit, Christoph Strecha, and Pascal Fua.
Brief: Binary robust independent elementary features.
In Proceedings of the 11th European Conference on Computer Vision: Part IV, ECCV'10, pages 778–792, Berlin, Heidelberg, 2010. Springer-Verlag.

CM09

S.L. Campbell and C.D. Meyer.
Generalized inverses of linear transformations.
Society for Industrial Mathematics, 2009.

CPS05

Ondra Chum, Tomás Pajdla, and Peter Sturm.
The Geometric Error for Homographies.
Computer Vision and Image Understanding, 97(1):86–102, January 2005.

CV95

Corinna Cortes and Vladimir Vapnik.
Support-vector networks.
Machine Learning, 20:273–297, 1995.
10.1007/BF00994018.

DF01

Frederic Devernay and Olivier D. Faugeras.
Straight lines have to be straight.
Machine Vision and Applications, 13(1):14–24, 2001.

DT05

Navneet Dalal and Bill Triggs.
Histograms of oriented gradients for human detection.
In Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01, CVPR '05, pages 886–893, Washington, DC, USA, 2005. IEEE Computer Society.

FB81

Martin A. Fischler and Robert C. Bolles.
Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography.
Communications of the ACM, 24(6):381–395, 1981.

FB87

Martin A. Fischler and Robert C. Bolles.
Readings in computer vision: issues, problems, principles, and paradigms.
chapter Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, pages 726–740. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 1987.

FG87

W. Förstner and E. Gülch.
A Fast Operator for Detection and Precise Location of Distinct Points, Corners and Centres of Circular Features, 1987.

FH94

Yoav Freund and David Haussler.
Unsupervised learning of distributions on binary vectors using two layer networks.
Technical report, Santa Cruz, CA, USA, 1994.

FHT00

J. Friedman, T. Hastie, and R. Tibshirani.
Additive Logistic Regression: a Statistical View of Boosting.
The Annals of Statistics, 38(2), 2000.

FK08

Robert B. Fisher and Kurt Konolige.
Range sensors.
In Bruno Siciliano and Oussama Khatib, editors, Springer Handbook of Robotics, pages 521–542. Springer, 2008.

FPF99

Andrew Fitzgibbon, Maurizio Pilu, and Robert B. Fisher.
Direct least square fitting of ellipses.
IEEE Trans. Pattern Anal. Mach. Intell., 21(5):476–480, May 1999.

FS95

Yoav Freund and Robert E. Schapire.
A decision-theoretic generalization of on-line learning and an application to boosting.
In Proceedings of the Second European Conference on Computational Learning Theory, pages 23–37, London, UK, 1995. Springer-Verlag.

GKSB10

G. Grisetti, R. Kuemmerle, C. Stachniss, and W. Burgard.
A tutorial on graph-based SLAM.
Intelligent Transportation Systems Magazine, IEEE, 2(4):31–43, 2010.

gre84

Iteratively reweighted least squares for maximum likelihood estimation, and some robust and resistant alternatives.
Journal of the Royal Statistical Society: Series B (Methodological), 46(2):149–170, 1984.

GVL96

Gene H. Golub and Charles F. Van Loan.
Matrix Computations (Johns Hopkins Studies in Mathematical Sciences)(3rd Edition).
The Johns Hopkins University Press, 3rd edition, October 1996.

GZS11

Andreas Geiger, Julius Ziegler, and Christoph Stiller.
Stereoscan: Dense 3d reconstruction in real-time.
In Intelligent Vehicles Symposium (IV), 2011.

Har95

R.I. Hartley.
In defence of the 8-point algorithm.
In Computer Vision, 1995. Proceedings., Fifth International Conference on, pages 1064–1070, June 1995.

Her08

Christoph Hertzberg.
A framework for sparse, non-linear least squares problems on manifolds, 2008.

Hin12

Geoffrey E. Hinton.
A practical guide to training restricted boltzmann machines.
In Grégoire Montavon, Genevieve B. Orr, and Klaus-Robert Müller, editors, Neural Networks: Tricks of the Trade (2nd ed.), volume 7700 of Lecture Notes in Computer Science, pages 599–619. Springer, 2012.

Hop82

J. J. Hopfield.
Neural networks and physical systems with emergent collective computational abilities.
Proceedings of the National Academy of Sciences of the United States of America, 79(8):2554–2558, apr 1982.

Hor87

Berthold K. P. Horn.
Closed-form solution of absolute orientation using unit quaternions.
Journal of the Optical Society of America A, 4(4):629–642, 1987.

HOT06

Geoffrey E. Hinton, Simon Osindero, and Yee-Whye Teh.
A fast learning algorithm for deep belief nets.
Neural Comput., 18(7):1527–1554, July 2006.

Hou59

P. V. C. Hough.
Machine Analysis of Bubble Chamber Pictures.
In International Conference on High Energy Accelerators and Instrumentation, CERN, 1959.

HR11

J. A. Hesch and S. I. Roumeliotis.
A direct least-squares (dls) method for pnp.
In 2011 International Conference on Computer Vision, pages 383–390, Nov 2011.

HS88

C. Harris and M. Stephens.
A combined corner and edge detector.
In Proceedings of the 4th Alvey Vision Conference, pages 147–151, 1988.

HS97

Richard I Hartley and Peter Sturm.
Triangulation.
Computer vision and image understanding, 68(2):146–157, 1997.

Hub96

P.J. Huber.
Robust statistical procedures.
CBMS-NSF regional conference series in applied mathematics. Society for Industrial and Applied Mathematics, 1996.

HZ04

R. I. Hartley and A. Zisserman.
Multiple View Geometry in Computer Vision.
Cambridge University Press, ISBN: 0521540518, second edition, 2004.

JU97

S.J. Julier and J.K. Uhlmann.
A new extension of the kalman filter to nonlinear systems.
In Int. Symp. Aerospace/Defense Sensing, Simul. and Controls, volume 3, page 26, 1997.

Kab76

Wolfgang Kabsch.
A solution for the best rotation to relate two sets of vectors.
Acta Crystallographica Section A: Crystal Physics, Diffraction, Theoretical and General Crystallography, 32(5):922–923, 1976.

KB14

Diederik P. Kingma and Jimmy Ba.
Adam: A method for stochastic optimization, 2014.

KHB09

Juho Kannala, Janne Heikkilä, and Sami S. Brandt.
Geometric camera calibration.
In In: Wah BW (ed.) Encyclopedia of Computer Science and Engineering., volume 3, pages 1389–1400. Wiley, Hoboken, NJ, 2009.

KK95

Yasushi Kanazawa and Kenichi Kanatani.
Reliability of 3-d reconstruction by stereo vision.
IEICE Transactions, 78-D(10):1301–1306, 1995.

KKLD23

Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis.
3d gaussian splatting for real-time radiance field rendering, 2023.

KSH12

Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton.
Imagenet classification with deep convolutional neural networks.
In F. Pereira, C. J. C. Burges, L. Bottou, and K. Q. Weinberger, editors, Advances in Neural Information Processing Systems 25, pages 1097–1105. Curran Associates, Inc., 2012.

LaV06

S. M. LaValle.
Planning Algorithms.
Cambridge University Press, Cambridge, U.K., 2006.
Available at http://planning.cs.uiuc.edu/.

LF97

Q.-T. Luong and O. D. Faugeras.
Self-calibration of a moving camera from pointcorrespondences and fundamental matrices.
Int. J. Comput. Vision, 22(3):261–289, 1997.

LFNP09

V. Lepetit, F.Moreno-Noguer, and P.Fua.
Epnp: An accurate o(n) solution to the pnp problem.
International Journal Computer Vision, 81(2), 2009.

Lin94

Tony Lindeberg.
Scale-Space Theory in Computer Vision.
Kluwer Academic Publishers, Norwell, MA, USA, 1994.

Lin10

Peter Lindstrom.
Triangulation made easy.
In CVPR, pages 1554–1561. IEEE Computer Society, 2010.

Lin14

Tony Lindeberg.
Scale selection.
In Katsushi Ikeuchi, editor, Computer Vision, pages 701–713. Springer US, 2014.

LK81

Bruce D. Lucas and Takeo Kanade.
An iterative image registration technique with an application to stereo vision.
In Proceedings of the 7th International Joint Conference on Artificial Intelligence - Volume 2, IJCAI'81, pages 674–679, San Francisco, CA, USA, 1981. Morgan Kaufmann Publishers Inc.

Lon81

Longuet.
A computer algorithm for reconstructing a scene from two projections.
Nature, 293:133–135, Sep. 1981.

Lou05

M I A Lourakis.
A brief description of the levenberg-marquardt algorithm implemened by levmar.
Matrix, 3:2, 2005.

Low04

David G. Lowe.
Distinctive image features from scale-invariant keypoints.
International Journal of Computer Vision, 60:91–110, 2004.

LS10

Philip M. Long and Rocco A. Servedio.
Random classification noise defeats all convex potential boosters.
Mach. Learn., 78(3):287–304, March 2010.

LZ99

Charles Loop and Zhengyou Zhang.
Computing rectifying homographies for stereo vision.
Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, 1:1125, 1999.

Mah36

P. C. Mahalanobis.
On the generalised distance in statistics.
In Proceedings National Institute of Science, India, volume 2, pages 49–55, April 1936.

MBLB91

H.A. Mallot, H.H. Bülthoff, JJ Little, and S. Bohrer.
Inverse perspective mapping simplifies optical flow computation and obstacle detection.
Biological cybernetics, 64(3):177–185, 1991.

MBT04

Kaj Madsen, Hans Bruun, and Ole Tingleff.
Methods for Non-Linear Least Squares Problems (2nd ed.).
Informatics and Mathematical Modelling, Technical University of Denmark, DTU, Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby, 2004.

MK04

Gerard Medioni and Sing Bing Kang.
Emerging Topics in Computer Vision.
Prentice Hall PTR, Upper Saddle River, NJ, USA, 2004.

Mor80

Hans Moravec.
Obstacle avoidance and navigation in the real world by a seeing robot rover.
In tech. report CMU-RI-TR-80-03, Robotics Institute, Carnegie Mellon University & doctoral dissertation, Stanford University, number CMU-RI-TR-80-03. September 1980.

MS02

Krystian Mikolajczyk and Cordelia Schmid.
An affine invariant interest point detector.
In Proceedings of the 7th European Conference on Computer Vision, Copenhagen, Denmark, pages 128–142. Springer, 2002.
Copenhagen.

MST$^+$20

Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng.
Nerf: Representing scenes as neural radiance fields for view synthesis.
CoRR, abs/2003.08934, 2020.

Nie99

H. B. Nielsen.
Damping parameter in marquardt's method.
Technical report, Informatics and Mathematical Modelling, Technical University of Denmark, DTU, Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby, apr 1999.

Nis04

David Nistér.
An efficient solution to the five-point relative pose problem.
IEEE Trans. Pattern Anal. Mach. Intell., 26(6):756–777, June 2004.

OPM02

Timo Ojala, Matti Pietikainen, and Topi Maenpaa.
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7):971–987, 2002.

PIK92

John Princen, John Illingworth, and Josef Kittler.
A formal definition of the hough transform: Properties and relationships.
Journal of Mathematical Imaging and Vision, pages 153–168, 1992.

PP99

Constantine Papageorgiou and Tomaso Poggio.
Trainable pedestrian detection.
In ICIP (4), pages 35–39, 1999.

RD05

Edward Rosten and Tom Drummond.
Fusing points and lines for high performance tracking.
In IEEE International Conference on Computer Vision, volume 2, pages 1508–1511, October 2005.

RD06

Edward Rosten and Tom Drummond.
Machine learning for high-speed corner detection.
In European Conference on Computer Vision, volume 1, pages 430–443, May 2006.

Rou84

Peter J. Rousseeuw.
Least Median of Squares Regression.
Journal of the American Statistical Association, 79(388):871–880, December 1984.

Rud16

Sebastian Ruder.
An overview of gradient descent optimization algorithms, 2016.

SF11

Davide Scaramuzza and Friedrich Fraundorfer.
Visual odometry [tutorial].
IEEE Robot. Automat. Mag., 18(4):80–92, 2011.

SM99

Peter Sturm and Steve Maybank.
On plane-based camera calibration: A general algorithm, singularities, applications.
In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Fort Collins, USA, pages 432–437, Juin 1999.

Smo86

P. Smolensky.
Parallel distributed processing: Explorations in the microstructure of cognition, vol. 1.
chapter Information Processing in Dynamical Systems: Foundations of Harmony Theory, pages 194–281. MIT Press, Cambridge, MA, USA, 1986.

SS02

B. Schölkopf and A.J. Smola.
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond.
Adaptive Computation and Machine Learning. Mit Press, 2002.

SSM06

G. Sibley, G. Sukhatme, and L. Matthies.
The iterated sigma point kalman filter with applications to long range stereo.
In Proceedings of Robotics: Science and Systems, Philadelphia, USA, August 2006.

ST94

J. Shi and C. Tomasi.
Good features to track.
In IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 593–600, Seattle, United States, June 1994.

Str87

Thomas M. Strat.
Readings in computer vision: issues, problems, principles, and paradigms.
chapter Recovering the camera parameters from a transformation matrix, pages 93–100. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 1987.

Sze10

Richard Szeliski.
Computer vision : Algorithms and applications.
Computer, 5:832, 2010.

TMHF00

Bill Triggs, Philip F. McLauchlan, Richard I. Hartley, and Andrew W. Fitzgibbon.
Bundle adjustment - a modern synthesis.
In Proceedings of the International Workshop on Vision Algorithms: Theory and Practice, ICCV '99, pages 298–372, London, UK, 2000. Springer-Verlag.

Tsa87

R. Tsai.
A versatile camera calibration technique for high-accuracy 3d machine vision metrology using off-the-shelf tv cameras and lenses.
Robotics and Automation, IEEE Journal of, 3(4):323–344, August 1987.

TSK06

Pang-Ning Tan, Michael Steinbach, and Vipin Kumar.
Introduction to Data Mining.
Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 2006.

Ume91

S. Umeyama.
Least-squares estimation of transformation parameters between two point patterns.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(4):376–380, 1991.

Val84

L. G. Valiant.
A theory of the learnable.
Commun. ACM, 27:1134–1142, November 1984.

VHV91

Sabine Van Huffel and Joos Vandewalle.
The Total Least Squares Problem.
Society for Industrial and Applied Mathematics, 1991.

VJ01

Paul Viola and Michael Jones.
Fast and robust classification using asymmetric adaboost and a detector cascade.
In Advances in Neural Information Processing System 14, pages 1311–1318. MIT Press, 2001.

VJ02

Paul Viola and Michael Jones.
Robust real-time object detection.
International Journal of Computer Vision, 57(2):137–154, 2002.

WB95

Greg Welch and Gary Bishop.
An introduction to the kalman filter.
Technical report, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA, 1995.

WM94

G. Q. Wei and S. D. Ma.
Implicit and explicit camera calibration: Theory and experiments.
IEEE Trans. Pattern Anal. Mach. Intell., 16(5):469–480, 1994.

YLT$^+$21

Alex Yu, Ruilong Li, Matthew Tancik, Hao Li, Ren Ng, and Angjoo Kanazawa.
PlenOctrees for real-time rendering of neural radiance fields.
In ICCV, 2021.

ZB17

Christopher Zach and Guillaume Bourmaud.
Iterated lifting for robust cost optimization.
In Gabriel Brostow Tae-Kyun Kim, Stefanos Zafeiriou and Krystian Mikolajczyk, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 86.1–86.11. BMVA Press, September 2017.

Zha99

Zhengyou Zhang.
Flexible camera calibration by viewing a plane from unknown orientations.
In Proceedings of the Seventh IEEE International Conference on Computer Vision., volume 1, pages 666–673 vol.1, 1999.

ZPvBG01

Matthias Zwicker, Hanspeter Pfister, Jeroen van Baar, and Markus Gross.
Surface splatting.
In Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH '01, pages 371–378, New York, NY, USA, 2001. Association for Computing Machinery.

ZW94

Ramin Zabih and John Woodfill.
Non-parametric local transforms for computing visual correspondence.
In ECCV (2), pages 151–158, 1994.