Akaike, H.[Hirotugu],
A new look at the statistical model identification,
AC(19), No. 6, 1974, pp. 716-723.
IEEE DOI
1001
Measurement of goodness of fit to a statistical model.
BibRef
Nielsen, L.[Lars],
Sparr, G.[Gunnar],
Projective Area-Invariants as an Extension of the Cross-Ratio,
CVGIP(54), No. 1, July 1991, pp. 145-159.
Elsevier DOI
BibRef
9107
Earlier: A2, A1:
Shape and mutual cross-ratios with applications to exterior, interior
and relative orientation,
ECCV90(607-609).
Springer DOI
9004
BibRef
Kanatani, K.[Kenichi],
Computational Cross Ratio for Computer Vision,
CVGIP(60), No. 3, November 1994, pp. 371-381.
DOI Link
BibRef
9411
Kanatani, K.[Kenichi],
Statistical Foundation for Hypothesis Testing of Image Data,
CVGIP(60), No. 3, November 1994, pp. 382-391.
DOI Link
BibRef
9411
Kanatani, K.[Kenichi],
Geometric Information Criterion for Model Selection,
IJCV(26), No. 3, March 1998, pp. 171-189.
DOI Link
9804
See also Statistical-Analysis of Geometric Computation.
BibRef
Kanatani, K.[Kenichi],
Uncertainty Modeling and Model Selection for Geometric Inference,
PAMI(26), No. 10, October 2004, pp. 1307-1319.
IEEE Abstract.
0409
Discuss the meaning of statistical methods for geometric inference.
Feature uncertainty from image processing operations.
Derive the geometric AIC and the geometric MDL as counterparts of
Akaike's AIC (
See also new look at the statistical model identification, A. ) and Rissanen's MDL (
See also Universal Prior for Integers and Esitmation by Minimum Description Length, A. ).
BibRef
Kanatani, K.[Kenichi],
Geometric BIC,
IEICE(E93-D), No. 1, January 2010, pp. 144-151.
WWW Link.
1001
Geometric fitting. Similar to geometric MDL.
BibRef
Kanatani, K.[Kenichi],
Further improving geometric fitting,
3DIM05(2-13).
IEEE DOI
0508
BibRef
Sapiro, G.,
Tannenbaum, A.,
Area and Length Preserving Geometric Invariant Scale-Spaces,
PAMI(17), No. 1, January 1995, pp. 67-72.
IEEE DOI
BibRef
9501
Earlier:
ECCV94(B:449-458).
Springer DOI
See also Affine Invariant Scale-Space.
BibRef
Maybank, S.J.,
Probabilistic Analysis of the Application of the Cross Ratio to
Model-Based Vision: Misclassification,
IJCV(14), No. 3, April 1995, pp. 199-210.
Springer DOI
BibRef
9504
Maybank, S.J.,
Probabilistic Analysis of the Application of the Cross Ratio
to Model-Based Vision,
IJCV(16), No. 1, September 1995, pp. 5-33.
Springer DOI
Evaluation, Cross Ratio. Analysis of the use of the cross ratio for matching. How does it vary
when the points have Gaussian distributions.
BibRef
9509
Maybank, S.J.,
Stochastic Properties of the Cross Ratio,
PRL(17), No. 3, March 6 1996, pp. 211-217.
BibRef
9603
Maybank, S.J.[Steven J.],
Relation Between 3D Invariants and 2D Invariants,
IVC(16), No. 1, January 30 1998, pp. 13-20.
Elsevier DOI
9803
BibRef
Earlier:
RVS95(xx).
BibRef
Maybank, S.J.[Steven J.],
Error Trade-Offs for the Cross-Ratio in Model Based Vision,
ConferenceWorkshop on Computer Vision for Space Applications 1993,
pp. 350-359. Antibes France.
BibRef
9300
Maybank, S.J.[Steven J.],
Fraile, R.,
Minimum description length method for facet matching,
PRAI(14), 2000, pp. 919-927.
BibRef
0001
Bribiesca, E.[Ernesto],
Measuring 3-D Shape Similarity Using Progressive Transformations,
PR(29), No. 7, July 1996, pp. 1117-1129.
Elsevier DOI
9607
Use Voxel representation.
Measure how much "information" in the representation.
Shape difference is how much work to trransform one to the other.
See also easy measure of compactness for 2D and 3D shapes, An.
See also Digital Elevation Model Data Analysis Using the Contact Surface Area.
BibRef
Sanchez-Cruz, H.[Hermilo],
Bribiesca, E.[Ernesto],
A method of optimum transformation of 3D objects used as a measure of
shape dissimilarity,
IVC(21), No. 12, November 2003, pp. 1027-1036.
Elsevier DOI
0310
BibRef
Chetverikov, D.,
Lerch, A.,
A Matching Algorithm for Motion Analysis of Dense Populations,
PRL(11), 1990, pp. 743-749.
BibRef
9000
Chetverikov, D.,
Lerch, A.,
A Multiresolution Algorithm for Rotation-Invariant Matching of
Planar Shapes,
PRL(13), September 1992, pp. 669-676.
BibRef
9209
Ciuti, V.,
Marola, G.,
Santerini, D.,
An Algorithm for the Localization of Rotated and Scaled Objects,
PRL(11), 1990, pp. 59-66.
BibRef
9000
Lei, G.,
Recognition of Planar Objects in 3-D Space from
Single Perspective Views Using Cross Ratio,
RA(6), 1990, pp. 432-437.
BibRef
9000
Weinshall, D.[Daphna],
Minimal Decomposition of Model-Based Invariants,
JMIV(10), No. 1, January 1999, pp. 75-85.
DOI Link
BibRef
9901
Lourakis, M.I.A.,
Halkidis, S.T.,
Orphanoudakis, S.C.,
Matching Disparate Views of Planar Surfaces Using Projective Invariants,
IVC(18), No. 9, June 2000, pp. 673-683.
Elsevier DOI
0004
BibRef
Earlier:
BMVC98(I: 94-104).
PS File.
BibRef
Adán, A.[Antonio],
Cerrada, C.[Carlos],
Feliu, V.[Vicente],
Global shape invariants: a solution for 3D free-form object
discrimination/identification problem,
PR(34), No. 7, July 2001, pp. 1331-1348.
Elsevier DOI
0105
See also Active object recognition based on Fourier descriptors clustering.
BibRef
Tien, S.C.[Shen-Chi],
Chia, T.L.[Tsorng-Lin],
Lu, Y.B.[Yi-Bin],
Using cross-ratios to model curve data for aircraft recognition,
PRL(24), No. 12, August 2003, pp. 2047-2060.
Elsevier DOI
0304
BibRef
Dibos, F.[Françoise],
Frosini, P.[Patrizio],
Pasquignon, D.[Denis],
The Use of Size Functions for Comparison of Shapes Through Differential
Invariants,
JMIV(21), No. 2, September 2004, pp. 107-118.
DOI Link
0409
Use size to reduce errors in invariants.
BibRef
Huynh, D.,
The Cross Ratio: A Revisit to its Probability Density Function,
BMVC00(xx-yy).
PDF File.
0009
BibRef
Wang, G.Y.[Guo-Yu],
Houkes, Z.,
Regtien, P.P.L.,
Korsten, M.J.,
Ji, G.,
A Statistical Model to Describe Invariants Extracted from a 3-D
Quadric Surface Patch and its Applications in Region-Based Recognition,
ICPR98(Vol I: 668-672).
IEEE DOI
9808
BibRef
Simon, D.A.[David A.],
Kanade, T.[Takeo],
Geometric Constraint Analysis and Synthesis:
Methods for Improving Shape-Based Registration Accuracy,
DARPA97(901-910).
BibRef
9700
Muresan, L.[Lucian],
2D-2D geometric transformation invariant to arbitrary translations,
rotations and scales,
CAIP97(90-97).
Springer DOI
9709
BibRef
Zribi, M.,
Fonga, H.,
Ghorbel, F.,
A Set of Invariant Features for Three-Dimensional Gray Level Objects
by Harmonic Analysis,
ICPR96(I: 549-553).
IEEE DOI
9608
(Ecole Nouvelle d'ingenierus, F)
BibRef
Lei, Z.B.[Zhi-Bin],
Tasdizen, T.[Tolga], and
Cooper, D.B.[David B.],
PIMs and Invariant Parts for Shape Recognition,
ICCV98(827-832).
IEEE DOI
BibRef
9800
Lei, Z.B.[Zhi-Bin],
Keren, D.,
Cooper, D.B.,
Computationally fast Bayesian recognition of complex objects based on
mutual algebraic invariants,
ICIP95(II: 635-638).
IEEE DOI
9510
BibRef
Cooper, D.B.[David B.],
Lei, Z.B.[Zhi-Bin],
On representation and invariant recognition of complex objects based on
patches and parts,
ORCV94(139-153).
Springer DOI
9412
BibRef
Sanfeliu, A.,
Llorens, A.,
Emde, W.,
Sensibility, Relative Error and Error Probability of Projective
Invariants of Planar Surfaces of 3D Objects,
ICPR92(I:328-331).
IEEE DOI
BibRef
9200
Yu, X.,
Bui, T.D., and
Krzyzak, A.,
Invariants and Pose Determination,
VF91(623-632).
Based on matching surface patches.
BibRef
9100
Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Invariants, Projective, Perspective .