Bibliography

1

A. Agarwal and B. Triggs.
Recovering 3D human pose from monocular images.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 28 (1), January 2006.

2

H. Akaike.
A new look at the statistical model identification.
IEEE Transactions on Automatic Control, 19: 716-723, 1974.

3

D. Allen.
Mean square error of prediction as a criterion for selecting variables.
Technometrics, 13: 469-475, 1971.

4

J. Aloimonos.
Shape from texture.
Biological Cybernetics, 58: 345-360, 1988.

5

S. Aouadi and L. Sarry.
Accurate and precise 2D-3D registration based on X-ray intensity.
Computer Vision and Image Understanding, 110: 134-151, 2008.

6

S. Arlot and A. Celisse.
A survey of cross-validation procedures for model selection.
Statistics Surveys, 4: 40-79, 2010.

7

K. V. Arya, P. Gupta, P. K. Kalra, and P. Mitra.
Image registration using robust M-estimators.
Pattern Recognition Letters, 28: 1957-1968, 2007.
ISSN 0167-8655.

8

M. Avriel and D. Wilde.
Optimality proof for the symmetric fibonacci search technique.
Fibonacci Quarterly, 4: 265-269, 1966.

9

S. Baker, R. Gross, and I. Matthews.
Lucas-Kanade 20 years on: A unifying framework.
International Journal of Computer Vision, 56: 221-255, 2004.

10

B. Bartczak, I. Schiller, C. Beder, and R. Koch.
Integration of a Time-of-Flight camera into a mixed reality system for handling dynamic scenes, moving viewpoints and occlusions in real-time.
In 3D Data Processing, Visualization and Transmission, 2008.

11

A. Bartoli.
Groupwise geometric and photometric direct image registration.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 30 (12): 2098-2108, December 2008a.

12

A. Bartoli.
Maximizing the predictivity of smooth deformable image warps through cross-validation.
Journal of Mathematical Imaging and Vision, 31 (2-3): 133-145, 2008b.

13

A. Bartoli.
Contributions to Image Registration and to the 3D Reconstruction of Rigid and Deformable Scenes (Habilitation à diriger des recherches).
PhD thesis, LASMEA UMR6602 - Université Blaise Pascal (Clermont 2), 2008c.

14

A. Bartoli and P. Sturm.
The 3D line motion matrix and alignment of line reconstruction.
International Journal of Computer Vision, 15: 501-517, 2004.

15

A. Bartoli and P. Sturm.
Structure-from-motion using lines: Representation, triangulation and bundle adjustment.
Computer Vision and Image Understanding, 100: 416-441, 2005.

16

A. Bartoli and A. Zisserman.
Direct estimation of non-rigid registrations.
In British Machine Vision Conference, 2004.

17

A. Bartoli, V. Gay-Bellile, U. Castellani, J. Peyras, S. Olsen, and P. Sayd.
Coarse-to-fine low-rank structure-from-motion.
In IEEE International Conference on Computer Vision and Pattern Recognition, 2008.

18

A. Bartoli, M. Perriollat, and S. Chambon.
Generalized thin-plate spline warps.
International Journal of Computer Vision, 88: 85-110, 2010.

19

H. Bay, T. Tuytelaars, and L. Van Gool.
SURF: Speeded up robust features.
In European Conference on Computer Vision, 2006.

20

H. Bay, A. Ess, T. Tuytelaars, and L. V. Gool.
SURF: Speeded up robust features.
Computer Vision and Image Understanding, 110: 346-359, 2008.

21

S. Benhimane and E. Malis.
Real-time image-based tracking of planes using efficient second-order minimization.
In Proceedings of the International Conference on Intelligent Robots and Systems, 2004.

22

Å. Björck.
Numerical Methods for Least Squares Problems.
Society for Industrial and Applied Mathematics, 1996.

23

A. Blake and A. Zisserman.
Visual Reconstruction.
MIT Press, 1987.

24

F. L. Bookstein.
Principal warps: Thin-plate splines and the decomposition of deformations.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 11 (6): 567-585, 1989.
ISSN 0162-8828.

25

S. Boyd and L. Vandenberghe.
Convex Optimization.
Cambridge University Press, 2004.

26

Y. Boykov, O. Veksler, and R. Zabih.
Fast approximate energy minimization via graph cuts.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 23: 1222-1239, 2001.

27

J. D. Brabanter, K. Pelckmans, J. Suykens, J. Vandewalle, and B. D. Moor.
Robust cross-validation score functions with application to weighted least squares support vector machine function estimation.
Technical report, Katholieke Universiteit Leuven, 2003.

28

M. Brand.
A direct method for 3D factorization of nonrigid motion observed in 2D.
In IEEE International Conference on Computer Vision and Pattern Recognition, 2005.

29

C. Bregler, A. Hertzmann, and H. Biermann.
Recovering non-rigid 3D shape from image streams.
In IEEE International Conference on Computer Vision and Pattern Recognition, pages 2690-2696, 2000.

30

F. Brunet.
Convolutions binomiales et dérivation de fonctions discrètes bruitées.
Master's thesis, Université Blaise Pascal, 2007.

31

F. Brunet, A. Bartoli, R. Malgouyres, and N. Navab.
L-Tangent Norm: A low computational cost criterion for choosing regularization weights and its use for range surface reconstruction.
In 3D Data Processing, Visualization and Transmission, 2008.

32

F. Brunet, A. Bartoli, N. Navab, and R. Malgouyres.
Ajustement automatique de surfaces paramétriques sur données de profondeur en présence d'un bruit hétérogène.
In Actes des journées COmpression et REprésentation des Signaux Audiovisuels, Mars 2009a.

33

F. Brunet, A. Bartoli, N. Navab, and R. Malgouyres.
Nurbs warps.
In British Machine Vision Conference, 2009b.

34

F. Brunet, A. Bartoli, J. Peyras, N. Navab, and R. Malgouyres.
Découverte automatique de la région d'intérêt en recalage d'images direct.
In Actes du onzième congrès francophone des jeunes chercheurs en vision par ordinateur, 2009c.

35

F. Brunet, A. Bartoli, N. Navab, and R. Malgouyres.
Utilisation de l'information photométrique pour la sélection des hyperparamètres en recalage géométrique d'images.
In Compression et représentation des signaux audiovisuels, 2010a.

36

F. Brunet, A. Bartoli, N. Navab, and R. Malgouyres.
Pixel-based hyperparameter selection for feature-based image registration.
In Vision, Modeling and Visualization Workshop, 2010b.

37

F. Brunet, A. Bartoli, N. Navab, and R. Malgouyres.
Découverte automatique du recouvrement en recalage direct d'images.
In Reconnaissance des Formes et Intelligence Artificielle, 2010c.

38

F. Brunet, A. Bartoli, N. Navab, and R. Malgouyres.
Direct image registration without region of interest.
In Vision, Modeling and Visualization Workshop, 2010d.

39

F. Brunet, R. Hartley, A. Bartoli, N. Navab, and R. Malgouyres.
Monocular template-based reconstruction of smooth and inextensible surfaces.
In Proceedings of the Tenth Asian Conference on Computer Vision (ACCV), Queenstown (New Zealand), November 2010e.

40

R. Burachik, L. Mauricio, G. Drummond, A. Iusem, and E. Castorina.
Full convergence of the steepest descent method with inexact line searches.
Optimization, 32: 137-146, 1996.

41

K. Burnham and D. Anderson.
Multimodel inference: Understanding AIC and BIC in model selection.
Sociological Methods Research, 33 (2): 261-304, 2004.

42

N. Carlson.
NURBS surface fitting with Gauss-Newton.
Master's thesis, Luleå University of Technology, 2009.

43

A. Cauchy.
Méthode générale pour la résolution des systèmes d'équations simultanées.
Comptes Rendus de Académie des Sciences, 25: 536-538, 1847.

44

CESAR laboratory (Oak Ridge National Laboratory).
USF Range Image Database.
http://marathon.csee.usf.edu/range/DataBase.html.

45

M. Cetin and A. Erar.
Variable selection with Akaike information criteria: a comparative study.
Hacettepe Journal of Mathematics and Statistics, 31: 89-97, 2002.

46

G. Chaitin.
On the length of programs for computing finite binary sequences.
Journal of the Association for Computing Machinery, 13: 547-569, 1966.

47

G. Charpiat, O. Faugeras, and R. Keriven.
Image statistics based on diffeomorphic matching.
In International Conference on Computer Vision, 2005.

48

A. Collignon, D. Vandermeulen, P. Suetens, and G. Marchal.
3d multi-modality medical image registration based on information theory.
Computational Imaging and Vision, 3: 263-274, 1995.

49

T. F. Cootes, G. J. Edwards, and C. J. Taylor.
Active appearance models.
In European Conference on Computer Vision, 1998.

50

T. Corpetti, E. Mémin, and P. Pérez.
Dense estimation of fluid flows.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 24: 365-380, 2002.

51

P. Craven and G. Wahba.
Smoothing noisy data with spline functions: estimating the correct degree of smoothing by the method of generalized cross-validation.
Numerische Mathematik, 31: 377-403, 1979.

52

J.-C. Culioli.
Introduction à l'optimisation.
Ellipses Marketing, 1994.

53

H. B. Curry and I. J. Schoenberg.
On spline distributions and their limits: the pólya distributions.
Bulletin of the American Mathematical Society, 53: 1114, 1947.

54

C. Dachapak, S. Kanae, Z. J. Yang, and K. Wada.
Study on radial basis function network in reproducing kernel Hilbert space.
In Signal and Image Processing, 2005.

55

T. A. Davis and W. W. Hager.
Modifying a sparse cholesky factorization.
SIAM Journal on Matrix Analysis and Applications, 20: 606-627, 1999.

56

C. de Boor.
On calculating with B-splines.
Journal of Approximation Theory, 6: 50-62, 1972.

57

C. de Boor.
A Practical Guide to Splines, Revised Edition, volume 27 of Applied Mathematical Sciences.
Springer, 2001.

58

A. Del Bue.
A factorization approach to structure from motion with shape priors.
In IEEE International Conference on Computer Vision and Pattern Recognition, 2008.

59

A. Del Bue and L. Agapito.
Non-rigid stereo factorization.
International Journal of Computer Vision, 66 (2): 193-207, 2006.

60

A. Del Bue and L. Agapito.
Scene Reconstruction, Pose Estimation and Tracking, chapter 14, pages 243-264.
2007.

61

P. Dierckx.
Curve and Surface Fitting with Splines.
Monographs on Numerical Analysis. Oxford University Press, 1993.

62

G. Donato and S. Belongie.
Approximation methods for thin plate spline mappings and principal warps.
In European Conference on Computer Vision. Springer, 2002.

63

A. Doshi, A. Hilton, and J. Starck.
An empirical study of non-rigid surface feature matching.
In European Conference on Visual Media Production, 2008.

64

J. Erickson, S. Har-Peled, and D. Mount.
On the least median square problem.
In 20th ACM Symposium on Computational Geometry, pages 273-279, 2004.

65

D. Falie and V. Buzuloiu.
Noise characteristics of 3D Time-of-Flight cameras.
In International Symposium on Signals, Circuits and Systems, 2007.

66

M. Farenzena, A. Bartoli, and Y. Mezouar.
Efficient camera smoothing in sequential structure-from-motion using approximate cross-validation.
In European Conference on Computer Vision, 2008.

67

G. Farin.
Curves and surfaces for computer-aided geometric design 4th Edition.
Computer Science and Scientific Computing. Academic Press, 1997.

68

O. Faugeras.
Three-Dimensional Computer Vision.
MIT, 1993.

69

O. Faugeras, Q.-T. Luong, and T. Papadopoulo.
The Geometry of Multiple Images.
MIT Press, 2004.

70

M. Fischler and B. Robert.
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.

71

G. Fleury and M. Gourgand.
Genetic algorithms applied to workshop problems.
International Journal of Computer Integrated Manufacturing, 11: 183-192, 1998.

72

M. Fornefett, K. Rohr, and H. Stiehl.
Elastic registration of medical images using radial basis functions with compact support.
In IEEE International Conference on Computer Vision and Pattern Recognition, 1999.

73

M. Fornefett, K. Rohr, and H. Stiehl.
Radial basis functions with compact support for elastic registration of medical images.
Image and Vision Computing, 19: 87-96, 2001.

74

V. Gay-Bellile.
Contributions au recalage et à la reconstruction 3D de surfaces déformables.
PhD thesis, Université Blaise Pascal, 2008.

75

V. Gay-Bellile, M. Perriollat, A. Bartoli, and P. Sayd.
Image registration by combining thin-plate splines with a 3D morphable model.
In IEEE International Conference on Image Processing, 2006.

76

V. Gay-Bellile, A. Bartoli, and P. Sayd.
Feature-driven direct non-rigid image registration.
In British Machine Vision Conference, 2007.

77

S. Geisser.
The predictive sample reuse method with applications.
Journal of the American Statistical Association, 70: 320-328, 1975.

78

C. P. Gendrich and M. M. Koochesfahani.
A spatial correlation technique for estimating velocity fields using molecular tagging velocimetry (mtv).
Experiments in Fluids, 22: 67-77, 1996.

79

J. Gentle, W. Härdle, and Y. Mori.
Handbook of Computational Statistics.
Springer, 2004.
URL http://fedc.wiwi.hu-berlin.de/xplore/ebooks/html/csa/.

80

S. George and M. T. Nair.
Parameter choice by discrepancy principles for ill-posed problems leading to optimal convergence rates.
Journal of Optimization theory and applications, 83 (1): 217-222, 1994.

81

P. Georgel, S. Benhimane, and N. Nassir.
A unified approach combining photometric and geometric information for pose estimation.
In British Machine Vision Conference, 2008.

82

S. B. Gokturk, H. Yalcin, and C. Bamji.
A time-of-flight depth sensor - system description, issues and solutions.
In IEEE International Conference on Computer Vision and Pattern Recognition, 2004.

83

G. Golub and C. F. Van Loan.
Matrix Computations.
The Johns Hopkins University Press, 1996a.

84

G. Golub and C. F. Van Loan.
Matrix Computations, chapter 5.2, pages 223-236.
The Johns Hopkins University Press, 1996b.

85

G. Golub, M. Health, and G. Wahba.
Generalized cross validation as a method for choosing a good ridge parameter.
Technometrics, 21: 215-223, 1979.

86

A. Gray.
Modern Differential Geometry of Curves and Surfaces with Mathematica, chapter The Gaussian and Mean Curvatures, pages 373-380.
CRC Press, 1997.

87

M. Groher, M. Baust, D. Zikic, and N. Navab.
Monocular deformable model-to-image registration of vascular structures.
In Proceedings of the International Workshop on Biomedical Image Registration (WBIR), 2010.

88

N. Gumerov, A. Zandifar, R. Duraiswami, and L. S. Davis.
Structure of applicable surfaces from single views.
In European Conference on Computer Vision, 2004.

89

E. Haber and J. Modersitzki.
Intensity gradient based registration and fusion of multi-modal images.
In S. Berlin, editor, International Conference on Medical Image Computing and Computer Assisted Intervention, volume 4191 of Lecture Notes in Computer Science, pages 726-733, 2006.

90

D. Hahn, V. Daum, and J. Hornegger.
Automatic parameter selection for multi-modal image registration.
IEEE Transactions on Medical Imaging, 29 (5): 1140-1155, 2010.

91

D. A. Hahn, Y. Sun, J. Hornegger, F. Sauer, G. Wolz, T. Kuwert, and X. Xu.
A practical salient region feature based 3D multimodality registration method for medical images.
Medical Imaging 2006: Image Processing, pages 870-879, 2006.

92

P. Hansen.
Analysis of discrete ill-posed problems by means of the L-curve.
SIAM Rev., 34 (4): 561-580, 1992.
ISSN 0036-1445.
doi: rmhttp://dx.doi.org/10.1137/1034115.

93

P. Hansen.
The L-curve and its use in the numerical treatment of inverse problems.
Technical report, Technical University of Denmark, 2005.
URL http://www.math.sintef.no/vskoler/2005/notes/Lcurve.pdf.

94

R. Hartley and A. Zisserman.
Multiple View Geometry in Computer Vision.
Cambridge University Press, second edition, 2003a.

95

R. Hartley and A. Zisserman.
Multiple View Geometry in Computer Vision, chapter A3, pages 568-577.
Cambridge University Press, second edition, 2003b.

96

T. Hastie, R. Tibshirani, and J. Friedman.
The Elements of Statistical Learning, chapter 8, pages 225-256.
Springer, 2001.

97

D. Heitz, P. Héaz, E. Mémin, and J. Carlier.
Dynamic consistent correlation-variational approach for robust optical flow estimation.
Experiments on Fluids, 45: 595-608, 2008.

98

B. K. P. Horn and B. G. Schunck.
Determining optical flow.
Artificial Intelligence, 17: 185-203, 1981.

99

S. Hsu, S. Acharya, A. Rafii, and R. New.
Performance of a Time-of-Flight camera for intelligent vehicle safety applications.
In Advanced Microsystems for Automotive Applications. 2006.

100

P. Huber.
Robust Statistics.
Wiley, 1981.

101

M. Irani and P. Anandan.
About direct methods.
In Workshop on Vision Algorithms, 1999.

102

H. J. Johnson and G. E. Christensen.
Consistent landmark and intensity-based image registration.
IEEE Transactions on Medical Imaging, 21 (5): 450-461, 2002.

103

S. Joshi and M. I. Miller.
Landmark matching via large deformation diffeomorphisms.
IEEE Transactions on Image Processing, 9: 1357-1370, 2000.

104

F. Jurie and M. Dhome.
Hyperplane approximation for template matching.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 24 (7): 996-1000, 2002.

105

T. Kanade and M. Okutomi.
A stereo matching algorithm with adaptive window: theory and experiment.
In IEEE International Conference on Robotics and Automation, 1991.

106

J. Kiefer.
Sequential minimax search for a maximum.
In Proceedings of the American Mathematical Society, volume 4, pages 502-506, 1953.

107

R. Koch, I. Schiller, B. Bartczak, F. Kellner, and K. Koeser.
MixIn3D: 3D mixed reality with ToF-cameras.
In Proceedings of the DAGM (German Association for Pattern Recognition) Syn3D Workshop, 2009.

108

A. Kolmogorov.
Three approaches to the quantitative definition of information.
Problems of Information Transmissions, 1: 1-7, 1965.

109

C. L. Lawson and R. J. Hanson.
Solving Least Squares Problem.
Prentice Hall, Englewood Cliffs, 1974.

110

K. Levenberg.
A method for the solution of certain non-linear problems in least squares.
The Quarterly of Applied Mathematics, 2: 164-168, 1944.

111

J. Lim and M.-H. Yang.
A direct method for non-rigid motion with thin-plate spline.
In IEEE International Conference on Computer Vision and Pattern Recognition, 2005.

112

T. Lindeberg and B. ter Haar Romeny.
Linear scale-space.
Mathematical Imaging and Vision. ter Haar Romeny, 1994.

113

J. A. Little, D. L. G. Hill, and D. J. Hawkes.
Deformations incorporating rigid structures.
Computer Vision and Image Understanding, 66 (2): 223-232, 1997.

114

D. G. Lowe.
Object recognition from local scale-invariant features.
In International Conference on Computer Vision, pages 1150-1157, 1999.

115

D. G. Lowe.
Distinctive image features from scale-invariant keypoints.
International Journal of Computer Vision, 60 (2): 91-110, 2004.

116

X. Luan.
Experimental Investigation of Photonic Mixer Device and Development of TOF 3D Ranging Systems Based on PMD Technology.
PhD thesis, University of Siegen, 2001.

117

K. Madsen, H. B. Nielsen, and O. Tingleff.
Methods for non-linear least squares problems, 2nd edition.
Technical University of Denmark, April 2004.

118

R. Malgouyres.
Algorithmes pour le synthèse d'images et l'animation 3D.
Collection Sciences Sup. Dunod, 2ème edition, 2005.

119

R. Malgouyres, F. Brunet, and S. Fourey.
Binomial convolutions and derivatives estimation from noisy discretizations.
In International Conference on Discrete Geometry for Computer Imagery, 2008.

120

C. Mallows.
Somme comments on cp.
Technometrics, 15 (4): 661-675, 1973.

121

D. Marquardt.
An algorithm for least-squares estimation of nonlinear parameters.
SIAM Journal on Applied Mathematics, 11: 431-441, 1963.

122

J. Matas, O. Chum, M. Urba, and T. Pajdla.
Robust wide baseline stereo from maximally stable extremal regions.
In British Machine Vision Conference, pages 384-396, 2002.

123

I. Matthews and S. Baker.
Active appearance models revisited.
International Journal of Computer Vision, 60 (2): 135-164, November 2004.

124

P. J. Mc Carthy.
Direct analytic model of the L-curve for thikhonov regularization parameter selection.
Inverse Problems, 19: 643-663, 2003.

125

C. R. Meyer, J. L. Boes, B. Kim, P. H. Bland, K. R. Zasadny, P. V. Kison, K. Koral, K. A. Frey, and R. L. Wahl.
Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations.
Medical Image Analysis, 1 (3): 195-206, 1997.

126

J. Michot, A. Bartoli, F. Gaspard, and J.-M. Lavest.
Algebraic line search for bundle adjustment.
In British Machine Vision Conference, 2009.

127

K. Mikolajczyk and C. Schmid.
A performance evaluation of local descriptors.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 27 (10): 1615-1630, 2005.

128

K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, F. Schaffalitzky, T. Kadir, and L. Van Gool.
A comparison of affine region detectors.
International Journal of Computer Vision, 65: 43-72, 2005.

129

J. Modersitzki.
Numerical Methods for Image Registration.
Oxford Science, 2004.

130

V. Morozov.
The error principle in the solution of operational equations by the regularization method.
Computational Mathematics and Mathematical Physics, 8: 63-87, 1966.

131

V. Nannen.
The paradox of overfitting.
Master's thesis, Dutch National Research Institute for Mathematics and Informatics, 2003a.

132

V. Nannen.
A short introduction to model selection, Kolmogorov complexity and Minimum Description Length (MDL).
Technical report, Dutch National Research Institute for Mathematics and Informatics, 2003b.

133

S. K. Nayar and Y. Nakagawa.
Shape from focus.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 16 (8): 824-831, 1994.

134

J. A. Nelder and R. Mead.
A simplex method for function minimization.
The Computer Journal, 7: 308-313, 1965.

135

D. Nistér and H. Stewénius.
Linear time maximally stable extremal regions.
In European Conference on Computer Vision, 2008.

136

J. Nocedal and S. J. Wright.
Numerical Optimization.
Springer, 1999.

137

J.-M. Odobez and P. Bouthemy.
Robust multiresolution estimation of parametric motion models.
Journal of Visual Communication and Image Representation, 6(4):348-365, December 1995., 6: 348-365, 1995.

138

S. Olsen and A. Bartoli.
Implicit non-rigid structure-from-motion with priors.
Journal of Mathematical Imaging and Vision, 31 (2-3): 233-244, 2008.

139

N. Papadakis and E. Mémin.
Variational assimilation of fluid motion from image sequence.
SIAM Journal on Imaging Science, 1: 343-363, 2008.

140

J. Penne, K. Höller, M. Stürmer, T. Schrauder, A. Schneider, R. Engelbrecht, H. Feußner, B. Schmauss, and J. Hornegger.
Time-of-Flight 3-D endoscopy.
In International Conference on Medical Image Computing and Computer Assisted Intervention, 2009.

141

S. Pereverzev and E. Schock.
Morozov's discrepancy principle for Tikhonov regularization of severely ill-posed problems in finite-dimensional subspaces.
Technical report, University of Kaiserslautern, 1999.

142

M. Perriollat and A. Bartoli.
A quasi-minimal model for paper-like surfaces.
In Proceedings of the ISPRS International Workshop ``Towards Benmarking Automated Calibration, Orientation, and Surface Reconstruction from Images'', 2007.

143

M. Perriollat, R. Hartley, and A. Bartoli.
Monocular template-based reconstruction of inextensible surfaces.
In British Machine Vision Conference, 2008.

144

M. Perriollat, R. Hartley, and A. Bartoli.
Monocular template-based reconstruction of inextensible surfaces.
International Journal of Computer Vision, 2010.

145

J. Pilet, V. Lepetit, and P. Fua.
Real-time non-rigid surface detection.
In IEEE International Conference on Computer Vision and Pattern Recognition, 2005.

146

J. Pilet, V. Lepetit, and P. Fua.
Fast non-rigid surface detection, registration and realistic augmentation.
International Journal of Computer Vision, 76 (2), 2008.

147

B. Pires and P. Aguiar.
Registration of images with small overlap.
IEEE Workshop on Multimedia Signal Processing, 2004.

148

D. Pizarro and A. Bartoli.
Shadow resistant direct image registration.
In Scandinavian Conference on Image Analysis, 2007.

149

D. Pizarro and A. Bartoli.
Feature-based deformable surface detection with self-occlusion reasoning.
In 3D Data Processing, Visualization and Transmission, 2010.

150

J. P. W. Pluim, J. B. A. Maintz, and M. A. Viergever.
Mutual information based registration of medical images: A survey.
IEEE Transactions on Medical Imaging, 22 (8): 986-1004, 2003.

151

T. Poggio, R. Rifkin, S. Mukherjee, and P. Niyogi.
General conditions for predictivity in learning theory.
Nature, 428: 419-422, 2004.

152

M. J. Powell.
Five lectures on radial basis functions.
Technical report, Informatics and Mathematical Modelling, Technical University of Denmark, DTU, 2005.
URL http://www2.imm.dtu.dk/pubdb/p.php?3600.

153

M. Prasad, A. Zisserman, and A. W. Fitzgibbon.
Single view reconstruction of curved surfaces.
In IEEE International Conference on Computer Vision and Pattern Recognition, volume 2, pages 1345-1354, June 2006.

154

W. Press, S. Teukolsky, W. Vetterling, and B. Flannery.
Numerical recipes in C (2nd ed.): the art of scientific computing.
Cambridge University Press, 1992.

155

J. Rissanen.
Modeling by the shortest data description.
Automatica, 14: 465-471, 1978.

156

S. Roberts and L. Stals.
Discrete thin plate spline smoothing in 3D.
In J. Crawford and A. J. Roberts, editors, Proceedings of 11th Computational Techniques and Applications Conference CTAC-2003, volume 45, pages C646-C659, 2004.

157

G. Rodriguez and D. Theis.
An algorithm for estimating the optimal regularization parameter by the L-curve.
Rendiconti di Matematica, 25: 69-84, 2005.

158

S. Romdhani and T. Vetter.
Efficient, robust and accurate fitting of a 3D morphable model.
In International Conference on Computer Vision, 2003.

159

E. Ronchetti.
Robustness aspects of model choice.
Statistica Sinica, 7: 327-338, 1997.

160

E. Ronchetti and R. Staudte.
A robust version of mallows's cp.
Journal of the American Statistical Association, 89 (426): 550-559, 1994.

161

P. Rousseeuw.
Least median of squares regression.
Journal of the American Statistical Association, 79 (388): 871-880, 1984.

162

D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes.
Nonrigid registration using free-form deformations: Application to breast MR images.
IEEE Transactions on Medical Imaging, 18: 712-721, 1999.

163

M. Salzmann, R. Hartley, and P. Fua.
Convex optimization for deformable surface 3-D tracking.
In International Conference on Computer Vision, 2007.

164

M. Salzmann, F. Moreno-Noguer, V. Lepetit, and P. Fua.
Closed-form solution to non-rigid 3D surface registration.
In European Conference on Computer Vision, pages 581-594, 2008a.

165

M. Salzmann, R. Urtasun, and P. Fua.
Local deformation models for monocular 3D shape recovery.
In IEEE International Conference on Computer Vision and Pattern Recognition, 2008b.

166

M. Salzmann, R. Urtasun, and P. Fua.
Local deformation models for monocular 3D shape recovery.
In IEEE International Conference on Computer Vision and Pattern Recognition, 2009.

167

D. Scharstein and R. Szeliski.
Stereo matching with nonlinear diffusion.
International Journal of Computer Vision, 28 (2): 155-174, 1998.

168

E. Schock.
Parameter choice by discrepancy principles for the approximate solution of ill-posed problems.
Integral Equations and Operator Theory, 7: 895-898, 1984.

169

I. J. Schoenberg.
Contributions to the problem of approximation of equidistant data by analytic functions.
Quarterly of Applied Mathematics, 4: 45-99, 1946.

170

L. Schumaker.
Spline functions: basic theory.
Wiley, 1981.

171

G. Schwarz.
Estimating the dimension of a model.
Annals of Statistics, 6: 461-464, 1978.

172

F. Schweiger, B. Zeisl, P. Georgel, G. Schroth, E. Steinbach, and N. Navab.
Maximum detector response markers for SIFT and SURF.
In Vision, Modeling and Visualization Workshop, 2009.

173

C. Shannon.
A mathematical theory of communication.
Bell System Technical Journal, 27: 379-423,623-656, 1948.

174

J. Shao.
Linear model selection by cross-validation.
Journal of the American Statistical Association, 88 (422): 486-494, 1993.

175

S. Shen, W. Shi, and Y. Liu.
Monocular template-based tracking of inextensible deformable surfaces under ${L}_{\mbox{2}}$-norm.
In Asian Conference on Computer Vision, pages 214-223, 2009.

176

S. Shen, W. Shi, and Y. Liu.
Monocular 3-D tracking of inextensible deformable surfaces under $L_2$-norm.
IEEE Transactions on Image Processing, 19: 512-521, 2010.

177

E. Shiguemori, H. de Campos Velho, and J. da Silva.
Generalized discrepancy principle.
In Inverse Problems, Design and Optimization Symposium, 2004.

178

G. Silveira and E. Malis.
Real-time visual tracking under arbitrary illumination changes.
In IEEE International Conference on Computer Vision and Pattern Recognition, 2007.

179

R. Solomonoff.
A formal theory of inductive inference, part 1 and 2.
Information and Control, 7: 1-22,224-254, 1964.

180

N. Sugiura.
Further analysis of the data by Akaike' s information criterion and the finite corrections.
Communications in Statistics - Theory and Methods, 7 (1): 13-26, 1978.

181

R. Szeliski.
Image alignment and stitching: A tutorial.
Foundations and Trends in Computer Graphics and Vision, 2: 1-104, 2006.

182

U. Tautenhahn and U. Hämarik.
The use of monotonicity for choosing the regularization parameter in ill-posed problems.
Inverse Problems, 15: 1487-1505, 1999.

183

A. Thompson and B. N. Taylor.
Guide for the Use of the International System of Units (SI), chapter 10, page 33.
National Institute of Standards and Technology, 2008.

184

C. Tomasi and L. Kanade.
Shape and motion from image streams under orthography: A factorization method.
International Journal of Computer Vision, 9: 137-154, 1992.

185

P. H. S. Torr and A. Zisserman.
Feature based methods for structure and motion estimation.
Vision Algorithms, 1999.

186

L. Torresani, A. Hertzmann, and C. Bregler.
Nonrigid structure-from-motion: Estimating shape and motion with hierarchical priors.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 30 (5): 878-892, 2008.

187

A. Turing.
On computable numbers, with an application to the entscheidungsproblem.
In Proceedings of the London Mathematical Society, 1936.

188

T. Tuytelaars and K. Mikolajczyk.
Local invariant feature detectors: A survey.
Foundations and Trends in Computer Graphics and Vision, 3 (3): 177-280, 2007.

189

C. Ulrich, C. Schaller, J. Penne, and J. Hornegger.
Evaluation of a time-of-flight based respiratory motion management system.
In Bildverarbeitung für die Medizin, 2010.

190

A. Vedaldi and B. Fulkerson.
VLFeat: An open and portable library of computer vision algorithms.
http://www.vlfeat.org/, 2008.

191

L. Viarani, D. Stoppa, L. Gonzo, M. Gottardi, and A. Simoni.
A CMOS smart pixel for active 3-D vision applications.
IEEE Sensors Journal, 4 (1): 145-152, 2004.

192

P. Viola.
Alignment by Maximization of Mutual Information.
PhD thesis, Massachusetts Institute of Technology, 1995.

193

G. Wahba.
Spline Models for Observational Data, volume 59 of CBMS-NSF Regional Conference Series in Applied Mathematics.
Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 1990.

194

G. Wahba and S. Wold.
A completely automatic French curve: fitting spline functions by cross-validation.
Commun. Stat., 4: 1-17, 1975.

195

J. Xiao, J. Chai, and T. Kanade.
A closed-form solution to non-rigid shape and motion recovery.
International Journal of Computer Vision, 67 (2): 233-246, 2006.

196

G. Xú and Z. Zhang.
Epipolar geometry in stereo, motion, and object recognition.
Springer, 1996.

197

Z. Xu, R. Schwarte, H. Heinol, B. Buxbaum, and T. Ringbeck.
Smart pixel - photonic mixer device (PMD).
Technical report, PMDTec, 2005.

198

R. Zabih and V. Kolmogorov.
Spatially coherent clustering using graph cuts.
In IEEE International Conference on Computer Vision and Pattern Recognition, 2004.

199

R. Zhang, P.-S. Tsai, J. E. Cryer, and M. Shah.
Shape from shading: A survey.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 21: 690-706, 1999.

200

S. Zhang.
High-resolution, Real-time 3-D Shape Measurement.
PhD thesis, Stony Brook University, 2005.

201

Z. Zhang.
Parameter estimation techniques: A tutorial with application to conic fitting.
Image and Vision Computing, 15: 59-76, 1997.

202

J. Zhu, S. Hoi, and M. Lyu.
Nonrigid shape recovery by gaussian process regression.
In IEEE International Conference on Computer Vision and Pattern Recognition, 2009.

203

D. Zikic, M. Baust, A. Kamen, and N. Navab.
Generalization of deformable registration in riemannian sobolev spaces.
In International Conference on Medical Image Computing and Computer Assisted Intervention, 2010a.

204

D. Zikic, B. Glocker, O. Kutter, M. Groher, N. Komodakis, A. Kamen, N. Paragios, and N. Navab.
Linear intensity-based image registration by markov random fields and discrete optimization.
Medical Image Analysis, In Press, Accepted Manuscript, 2010b.

205

B. Zitová and J. Flusser.
Image registration methods: a survey.
Image and Vision Computing, 21 (11): 977-1000, 2003.