Eggert, D.W.,
Lorusso, A.,
Fisher, R.B.,
Estimating 3-D Rigid-Body Transformations:
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MVA(9), No. 5-6, 1997, pp. 272-290.
Springer DOI
9705
BibRef
Edinburgh
Pose Estimation.
Evaluation, Pose. Euclidean transform from matched points.
For an earlier conference version:
PS File.
BibRef
Lorusso, A.,
Eggert, D.W., and
Fisher, R.B.,
A Comparison of Four Algorithms for Estimating 3-D
Rigid Transformations,
BMVC95(xx).
PDF File.
9509
BibRef
And:
DAI-No. 765, July 1995.
BibRef
Earlier:
DAI-No. 737, March 1995.
BibRef
Edinburgh
BibRef
Madsen, C.B.,
A Comparative-Study of the Robustness of Two Pose Estimation Techniques,
MVA(9), No. 5-6, 1997, pp. 291-303.
Springer DOI
9705
BibRef
Earlier:
PERF96(XX-YY).
HTML Version.
Evaluation, Matching.
BibRef
Liu, Y.[Yong],
Madsen, C.B.[Claus B.],
Störring, M.[Moritz],
An Extended Perspective Three Points Problem,
SCIA03(75-82).
Springer DOI
0310
BibRef
Aggarwal, J.K.,
Ghosh, J.,
Nair, D., and
Taha, I.,
A Comparative Study of Three Paradigms for Object Recognition:
Bayesian Statistics, Neural Networks, and Expert Systems,
AIU96(241-262).
Bayes Networks.
Neural Networks.
Expert Systems.
Evaluation.
BibRef
9600
Nair, D.,
Mitiche, A.,
Aggarwal, J.K.,
On comparing the performance of object recognition systems,
ICIP95(II: 631-634).
IEEE DOI
9510
BibRef
Walker, R.[Robert],
Evaluating the Performance of Spatially Explicit Models,
PhEngRS(69), No. 11, November 2003, pp. 1271-1278.
DOI Link Statistical approaches to evaluating the performance of spatially explicit models are described.
0401
BibRef
Mikolajczyk, K.,
Schmid, C.,
A Performance Evaluation of Local Descriptors,
PAMI(27), No. 10, October 2005, pp. 1615-1630.
IEEE DOI
0509
BibRef
Earlier:
CVPR03(II: 257-263).
IEEE DOI
0307
Award, Longuet-Higgins.
SIFT descriptors do best.
See also Distinctive Image Features from Scale-Invariant Keypoints.
BibRef
Rigamonti, R.[Roberto],
Lepetit, V.[Vincent],
González, G.[Germán],
Türetken, E.[Engin],
Benmansour, F.[Fethallah],
Brown, M.A.[Matthew A.],
Fua, P.[Pascal],
On the relevance of sparsity for image classification,
CVIU(125), No. 1, 2014, pp. 115-127.
Elsevier DOI
1406
Sparse representations
BibRef
Rigamonti, R.[Roberto],
Brown, M.A.[Matthew A.],
Lepetit, V.[Vincent],
Are sparse representations really relevant for image classification?,
CVPR11(1545-1552).
IEEE DOI
1106
Conclusion: enforcing sparsity constraints actually does not
improve recognition performance.
BibRef
Kanwal, N.[Nadia],
Bostanci, E.[Erkan],
Clark, A.F.[Adrian F.],
Evaluation Method, Dataset Size or Dataset Content:
How to Evaluate Algorithms for Image Matching?,
JMIV(55), No. 3, July 2016, pp. 378-400.
Springer DOI
1604
What matters in evaluation.
BibRef
Ruiz-Lendínez, J.J.[Juan José],
Ariza-López, F.J.[Francisco Javier],
Ureńa-Cámara, M.A.[Manuel Antonio],
Expert Knowledge as Basis for Assessing an Automatic Matching
Procedure,
IJGI(10), No. 5, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Ge, Y.H.[Yun-Hao],
Xiao, Y.[Yao],
Xu, Z.[Zhi],
Wang, X.R.[Xing-Rui],
Itti, L.[Laurent],
Contributions of Shape, Texture, and Color in Visual Recognition,
ECCV22(XII:369-386).
Springer DOI
2211
BibRef
Weibel, J.B.[Jean-Baptiste],
Rohrböck, R.[Rainer],
Vincze, M.[Markus],
Measuring the Sim2Real Gap in 3D Object Classification for Different 3D
Data Representation,
CVS21(107-116).
Springer DOI
2109
BibRef
Shah, M.A.[Muhammad A.],
Olivier, R.[Raphael],
Raj, B.[Bhiksha],
Optimal Strategies For Comparing Covariates To Solve Matching
Problems,
ICPR21(10622-10628)
IEEE DOI
2105
Measurement, Machine learning, Probabilistic logic, Data models,
Task analysis, Probes, Optimal matching
BibRef
Fonaryov, M.[Mark],
Lindenbaum, M.[Michael],
On the Minimal Recognizable Image Patch,
ICPR21(6734-6741)
IEEE DOI
2105
Evaluation of accuracy with occlusions.
Image recognition, Tools, Character recognition, Task analysis,
Materials requirements planning
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Temel, D.,
Lee, J.,
Al Regib, G.,
Object Recognition Under Multifarious Conditions: A Reliability
Analysis and a Feature Similarity-Based Performance Estimation,
ICIP19(3033-3037)
IEEE DOI
1910
object dataset, controlled experiment with recognition platforms,
feature similarity
BibRef
Mukhaimar, A.[Ayman],
Tennakoon, R.[Ruwan],
Lai, C.Y.[Chow Yin],
Hoseinnezhad, R.[Reza],
Bab-Hadiashar, A.[Alireza],
Comparative Analysis of 3D Shape Recognition in the Presence of Data
Inaccuracies,
ICIP19(2471-2475)
IEEE DOI
1910
Shapes into meaningful categories.
3D classification, neural networks, point cloud classification,
robust 3D classification
BibRef
Molinari, D.[Dario],
Pasquale, G.[Giulia],
Natale, L.[Lorenzo],
Caputo, B.[Barbara],
Automatic Creation of Large Scale Object Databases from Web Resources:
A Case Study in Robot Vision,
CIAP19(II:488-498).
Springer DOI
1909
BibRef
Guo, Z.Y.[Zhen-Yu],
Wang, Z.J.[Z. Jane],
An Adaptive Descriptor Design for Object Recognition in the Wild,
ICCV13(2568-2575)
IEEE DOI
1403
domain adaptation; image descriptor; multiple kernel learning
BibRef
Vreeswijk, D.T.J.[Daan T.J.],
Snoek, C.G.M.[Cees G.M.],
van de Sande, K.E.A.[Koen E.A.],
Smeulders, A.W.M.[Arnold W.M.],
All vehicles are cars: subclass preferences in container concepts,
ICMR12(8).
DOI Link
1301
humans bias labeling images with a container label
BibRef
Barnard, K.[Kobus],
Yanai, K.[Keiji],
Johnson, M.[Matthew],
Gabbur, P.[Prasad],
Cross Modal Disambiguation,
CLOR06(238-257).
Springer DOI
0711
BibRef
Barnard, K.[Kobus],
Duygulu, P.[Pinar],
Guru, R.,
Gabbur, P.,
Forsyth, D.A.[David A.],
The effects of segmentation and feature choice in a translation model
of object recognition,
CVPR03(II: 675-682).
IEEE DOI
0307
BibRef
Böttger, T.[Tobias],
Ulrich, M.[Markus],
Steger, C.T.[Carsten T.],
Subpixel-Precise Tracking of Rigid Objects in Real-Time,
SCIA17(I: 54-65).
Springer DOI
1706
BibRef
Wiedemann, C.[Christian],
Ulrich, M.[Markus],
Steger, C.T.[Carsten T.],
Recognition and Tracking of 3D Objects,
DAGM08(xx-yy).
Springer DOI
0806
BibRef
Ulrich, M.[Markus],
Steger, C.T.[Carsten T.],
Performance Comparison of 2D Object Recognition Techniques,
PCV02(A: 368).
0305
BibRef
Ulrich, M.[Markus],
Steger, C.T.[Carsten T.],
Empirical Performance Evaluation of Object Recognition Methods,
EEMCV01(xx-yy).
0110
BibRef
Mundy, J.L., and
Heller, A.J.,
The Evolution and Testing of a Model-Based Object Recognition System,
ICCV90(268-282).
IEEE DOI
BibRef
9000
Heller, A.J., and
Mundy, J.L.,
Benchmark Evaluation of a Model-Based Object Recognition System,
DARPA90(727-741).
Matching, Evaluation.
Benchmarks.
BibRef
9000
Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
Object Recognition, Retrieval Datasets .