13.4.5 Object Recognition Evaluation

Chapter Contents (Back)
Evaluation, Recognition.

Eggert, D.W., Lorusso, A., Fisher, R.B.,
Estimating 3-D Rigid-Body Transformations: A Comparison of Four Major Algorithms,
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 Nets. 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. Statistical approaches to evaluating the performance of spatially explicit models are described.
WWW Link. 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


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 .


Last update:Nov 18, 2017 at 20:56:18