P. Absil, R. Mahony, and R. Sepulchre, Optimization Algorithms on Matrix Manifolds, 2008.
DOI : 10.1515/9781400830244

URL : http://hdl.handle.net/1885/17178

H. A. Almohamad and S. O. Duffuaa, A linear programming approach for the weighted graph matching problem, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.15, issue.5, 1993.
DOI : 10.1109/34.211474

N. Ayache and O. D. Faugeras, HYPER: A New Approach for the Recognition and Positioning of Two-Dimensional Objects, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.8, issue.1, pp.44-54, 1986.
DOI : 10.1109/TPAMI.1986.4767751

D. H. Ballard and C. M. Brown, Computer Vision, 1982.

A. Berg, Shape Matching and Object Recognition, 2005.
DOI : 10.1007/11957959_25

A. Berg, T. Berg, and J. Malik, Shape Matching and Object Recognition Using Low Distortion Correspondences, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.435-439, 2005.
DOI : 10.1109/CVPR.2005.320

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.72.8044

A. C. Berg, T. L. Berg, and J. Malik, Shape Matching and Object Recognition Using Low Distortion Correspondences, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
DOI : 10.1109/CVPR.2005.320

S. Birchfield, KLT: An implementation of the Kanade-Lucas-Tomasi feature tracker, 1998.

O. Boiman, E. Schechtman, and M. Irani, In defense of Nearest-Neighbor based image classification, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587598

L. Bourdev and J. Malik, Poselets: Body part detectors trained using 3D human pose annotations, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459303

Y. Boureau, F. Bach, Y. Lecun, and J. Ponce, Learning mid-level features for recognition, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5539963

Y. Boykov, O. Veksler, and R. Zabih, Fast approximate energy minimization via graph cuts, pp.1222-1239, 2001.

T. Caetano, L. Cheng, Q. V. Le, and A. J. Smola, Learning graph matching, ICCV, 2007.

B. Caputo and L. Jie, A performance evaluation of exact and approximate match kernels for object recognition, ELCVIA, vol.8, pp.15-26, 2009.

R. L. Carroll, Vertebrate Paleontology and Evolution, 1988.

C. Chih, C. J. Chang, and . Lin, LIBSVM: a library for support vector machines, 2001.

O. Chapelle, Training a Support Vector Machine in the Primal, Neural Computation, vol.6, issue.5, 2007.
DOI : 10.1198/106186005X25619

T. Cour, P. Srinivasan, and J. Shi, Balanced graph matching, NIPS 19, 2007.

G. Csurka, C. Bray, C. Dance, and L. Fan, Visual categorization with bags of keypoints, ECCV Workshop on Statistical Learning in Computer Vision, 2004.

N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
DOI : 10.1109/CVPR.2005.177

URL : https://hal.archives-ouvertes.fr/inria-00548512

N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
DOI : 10.1109/CVPR.2005.177

URL : https://hal.archives-ouvertes.fr/inria-00548512

O. Duchenne, A. Joulin, and J. Ponce, A graph-matching kernel for object categorization, 2011 International Conference on Computer Vision, 2011.
DOI : 10.1109/ICCV.2011.6126445

URL : https://hal.archives-ouvertes.fr/hal-00650345

O. Duchenne, F. Bach, I. Kweon, and J. Ponce, A tensor-based algorithm for high-order graph matching, CVPR, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01063322

O. Duchenne, I. Laptev, J. Sivic, F. Bach, and J. Ponce, Automatic annotation of human actions in video, 2009 IEEE 12th International Conference on Computer Vision, pp.1491-1498, 2009.
DOI : 10.1109/ICCV.2009.5459279

O. Duchenne, F. Bach, I. Kweon, and J. Ponce, A tensor-based algorithm for high-order graph matching, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01063322

O. D. Faugeras and M. Hebert, A 3-d recognition and positioning algorithm using geometrical matching between primitive surfaces, Proceedings of the Eighth international joint conference on Artificial intelligence, pp.996-1002, 1983.

P. Felzenszwalb and D. Huttenlocher, Pictorial Structures for Object Recognition, International Journal of Computer Vision, vol.61, issue.1, pp.55-79, 2005.
DOI : 10.1023/B:VISI.0000042934.15159.49

P. Felzenszwalb and D. Huttenlocher, Pictorial Structures for Object Recognition, International Journal of Computer Vision, vol.61, issue.1
DOI : 10.1023/B:VISI.0000042934.15159.49

P. Felzenszwalb, D. Mcallester, and D. Ramanan, A discriminatively trained, multiscale, deformable part model, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587597

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.686

P. Felzenszwalb, R. Girshick, D. Mcallester, and D. Ramanan, Object Detection with Discriminatively Trained Part-Based Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.9, 2010.
DOI : 10.1109/TPAMI.2009.167

P. Felzenszwalb, D. Mcallester, and D. Ramanan, A discriminatively trained, multiscale, deformable part model, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587597

F. Pedro, D. P. Felzenszwalb, and . Huttenlocher, Efficient belief propagation for early vision, IJCV, vol.70, pp.41-54, 2006.

P. F. Felzenszwalb, R. B. Girshick, D. Mcallester, and D. Ramanan, Object Detection with Discriminatively Trained Part-Based Models, CVPR, 2008.
DOI : 10.1109/TPAMI.2009.167

R. Fergus, L. Fei-fei, P. Perona, and A. Zisserman, Learning object categories from Google's image search, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005.
DOI : 10.1109/ICCV.2005.142

R. Fergus, P. Perona, and A. Zisserman, Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition, International Journal of Computer Vision, vol.20, issue.1, pp.273-303, 2006.
DOI : 10.1007/s11263-006-8707-x

R. Fergus, P. Perona, and A. Zisserman, Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition, International Journal of Computer Vision, vol.20, issue.1, pp.71273-303, 2007.
DOI : 10.1007/s11263-006-8707-x

M. Fischler and R. Bolles, Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, Communications of the ACM, vol.24, issue.6, pp.381-395, 1981.
DOI : 10.1145/358669.358692

M. A. Fischler and R. A. Elschlager, The Representation and Matching of Pictorial Structures, IEEE Transactions on Computers, vol.22, issue.1, pp.67-92, 1973.
DOI : 10.1109/T-C.1973.223602

M. A. Fischler and R. A. Elschlager, The Representation and Matching of Pictorial Structures, IEEE Transactions on Computers, vol.22, issue.1, pp.67-92, 1973.
DOI : 10.1109/T-C.1973.223602

G. Frobenius, Ueber matrizen aus nicht negativen elementen, Sitzungsber. Königl. Preuss. Akad. Wiss, pp.456-477, 1912.

P. Gehler and S. Nowozin, On feature combination for multiclass object classication, ICCV, 2009.

K. Grauman and T. Darrell, Pyramid Match Hashing: Sub-Linear Time Indexing Over Partial Correspondences, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383225

G. Griffin, A. Holub, and P. Perona, Caltech-256 object category dataset, 2007.

G. Griffin, A. Holub, and P. Perona, Caltech-256 object category dataset, 2007.

W. E. Grimson and T. Lozano-perez, Model-Based Recognition and Localization from Sparse Range or Tactile Data, The International Journal of Robotics Research, vol.3, issue.3, pp.3-35, 1984.
DOI : 10.1177/027836498400300301

W. E. Grimson and T. Lozano-pérez, Localizing Overlapping Parts by Searching the Interpretation Tree, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.9, issue.4, pp.469-482, 1987.
DOI : 10.1109/TPAMI.1987.4767935

C. Gu, J. Lim, P. Arbelaez, and J. Malik, Recognition using regions, CVPR, 2009.

P. Daniel, S. Huttenlocher, and . Ullman, Object recognition using alignment, ICCV, 1987.

D. P. Huttenlocher and S. Ullman, Object recognition using alignment, ICCV, 1987.

H. Ishikawa, Exact optimization for markov random fields with convex priors, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.10, pp.1333-1336, 2003.
DOI : 10.1109/TPAMI.2003.1233908

H. Jegou, M. Douze, and C. Schmid, Improving Bag-of-Features for Large Scale Image Search, International Journal of Computer Vision, vol.42, issue.3, pp.313-336, 2010.
DOI : 10.1007/s11263-009-0285-2

URL : https://hal.archives-ouvertes.fr/inria-00514760

A. Joulin, F. Bach, and J. Ponce, Multi-class cosegmentation, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012.
DOI : 10.1109/CVPR.2012.6247719

URL : https://hal.archives-ouvertes.fr/hal-00717448

. Ho-yub-jung, S. U. Kyoung-mu-lee, and . Lee, Toward global minimum through combined local minima, ECCV, 2008.

J. Kim and K. Grauman, Asymmetric region-to-image matching for comparing images with generic object categories, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5539923

V. Kolmogorov, Convergent Tree-Reweighted Message Passing for Energy Minimization, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.10, pp.1568-1583, 2006.
DOI : 10.1109/TPAMI.2006.200

V. Kolmogorov and R. Zabih, What energy functions can be minimized via graph cuts? PAMI, pp.147-159, 2004.
DOI : 10.1109/tpami.2004.1262177

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.113.1823

A. Kushal, C. Schmid, and J. Ponce, Flexible Object Models for Category-Level 3D Object Recognition, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383149

URL : https://hal.archives-ouvertes.fr/inria-00548682

M. Lades, J. C. Vorbruggen, J. Buhmann, J. Lange, C. Der-malsburg et al., Distortion invariant object recognition in the dynamic link architecture, IEEE Transactions on Computers, vol.42, issue.3, pp.300-311, 1993.
DOI : 10.1109/12.210173

M. F. Land and R. D. Fernald, The Evolution of Eyes, Annual Review of Neuroscience, vol.15, issue.1, pp.1-29, 1992.
DOI : 10.1146/annurev.ne.15.030192.000245

L. De-lathauwer, B. De, J. Moor, and . Vandewalle, ) Approximation of Higher-Order Tensors, SIAM Journal on Matrix Analysis and Applications, vol.21, issue.4
DOI : 10.1137/S0895479898346995

S. Lazebnik, C. Schmid, and J. Ponce, A maximum entropy framework for partbased texture and object recognition, Proc. Int. Conf. Comp. Vision, volume I, pp.832-838, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00548510

S. Lazebnik, C. Schmid, and J. Ponce, Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), 2006.
DOI : 10.1109/CVPR.2006.68

URL : https://hal.archives-ouvertes.fr/inria-00548585

S. Lazebnik, C. Schmid, and J. Ponce, Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), 2006.
DOI : 10.1109/CVPR.2006.68

URL : https://hal.archives-ouvertes.fr/inria-00548585

S. Lazebnik, C. Schmid, and J. Ponce, A sparse texture representation using affine-invariant regions, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., pp.319-326, 2003.
DOI : 10.1109/CVPR.2003.1211486

URL : https://hal.archives-ouvertes.fr/inria-00548232

D. Lemire, Streaming maximum-minimum filter using no more than three comparisons per element, Nordic Journal of Computing, vol.13, issue.4, pp.328-339, 2006.

M. Leordeanu and M. Hebert, A spectral technique for for correspondance problems using pairwise constraints, ICCV, 2005.

M. Leordeanu and M. Hebert, A spectral technique for correspondence problems using pairwise constraints, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005.
DOI : 10.1109/ICCV.2005.20

M. Leordeanu, M. Hebert, and R. Sukthankar, Beyond Local Appearance: Category Recognition from Pairwise Interactions of Simple Features, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383091

C. Liu, J. Yuen, A. Torralba, J. Sivic, and W. T. Freeman, SIFT Flow: Dense Correspondence across Different Scenes, ECCV, 2008.
DOI : 10.1007/978-3-540-88690-7_3

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.3060

D. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004.
DOI : 10.1023/B:VISI.0000029664.99615.94

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

D. G. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004.
DOI : 10.1023/B:VISI.0000029664.99615.94

J. Maciel and J. Costeira, A global solution to sparse correspondence problems, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.2, 2003.
DOI : 10.1109/TPAMI.2003.1177151

T. Malisiewicz, A. Gupta, and A. A. Efros, Ensemble of exemplar-SVMs for object detection and beyond, 2011 International Conference on Computer Vision, 2011.
DOI : 10.1109/ICCV.2011.6126229

R. Oliveira, R. Ferreira, and J. Costeira, Optimal Multi-frame Correspondence with Assignment Tensors, Proc. European Conf. Comp. Vision, 2006.
DOI : 10.1007/11744078_38

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.104.5129

P. Pritchett and A. Zisserman, Wide baseline stereo matching, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), 1998.
DOI : 10.1109/ICCV.1998.710802

P. A. Regalia and E. Kofidis, The higher-order power method revisited: convergence proofs and effective initialization, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2000.
DOI : 10.1109/ICASSP.2000.861047

E. H. Rosch, Natural categories, Cognitive Psychology, vol.4, issue.3, pp.328-35090017, 1973.
DOI : 10.1016/0010-0285(73)90017-0

C. Schmid and R. Mohr, Local grayvalue invariants for image retrieval, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.19, issue.5, pp.530-535, 1997.
DOI : 10.1109/34.589215

URL : https://hal.archives-ouvertes.fr/inria-00548358

A. Shekhovtsov, I. Kovtun, and V. Hlavac, Efficient MRF deformation model for non-rigid image matching, CVIU, vol.112, pp.91-99, 2008.

J. Sivic and A. Zisserman, Video Google: a text retrieval approach to object matching in videos, Proceedings Ninth IEEE International Conference on Computer Vision, pp.1470-1477, 2003.
DOI : 10.1109/ICCV.2003.1238663

S. Todorovic and N. Ahuja, Learning subcategory relevances for category recognition, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587366

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.139.1690

S. Umeyama, An eigendecomposition approach to weighted graph matching problems, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.10, issue.5, pp.695-703, 1988.
DOI : 10.1109/34.6778

W. Vanduffel, R. B. Tootell, A. A. Schoups, and G. A. Orban, The Organization of Orientation Selectivity Throughout Macaque Visual Cortex, Cerebral Cortex, vol.12, issue.6, pp.647-662, 2002.
DOI : 10.1093/cercor/12.6.647

M. Varma and D. Ray, Learning The Discriminative Power-Invariance Trade-Off, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408875

A. Vedaldi, A matlab implementation of sift, 2008.

P. Viola and M. J. Jones, Robust Real-Time Face Detection, International Journal of Computer Vision, vol.57, issue.2, pp.137-154, 2004.
DOI : 10.1023/B:VISI.0000013087.49260.fb

M. Wainwright, T. Jaakkola, and A. Willsky, Exact map estimates by (hyper)tree agreement, NIPS, 2002.

C. Wallraven, B. Caputo, and A. Graf, Recognition with local features: the kernel recipe, Proceedings Ninth IEEE International Conference on Computer Vision, 2003.
DOI : 10.1109/ICCV.2003.1238351

G. Wu, E. Y. Chang, and Z. Zhang, An analysis of transformation on non-positive semidefinite similarity matrix for kernel machines, Proceedings of the 22nd International Conference on Machine Learning, 2005.

J. Yang, Y. Li, Y. Tian, L. Duan, and W. Gao, Group-sensitive multiple kernel learning for object categorization, ICCV, 2009.

J. Yang, K. Yu, and T. Huang, Efficient Highly Over-Complete Sparse Coding Using a Mixture Model, ECCV, 2010.
DOI : 10.1007/978-3-642-15555-0_9

J. Yang, K. Yu, Y. Gong, and T. Huang, Linear spatial pyramid matching using sparse coding for image classification, CVPR, 2009.

A. L. Yuille, Deformable Templates for Face Recognition, Journal of Cognitive Neuroscience, vol.26, issue.2, pp.59-70, 1991.
DOI : 10.1068/p130505

M. Zaslavskiy, F. Bach, and J. P. Vert, A Path Following Algorithm for the Graph Matching Problem, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.12, pp.312227-2242, 2009.
DOI : 10.1109/TPAMI.2008.245

URL : https://hal.archives-ouvertes.fr/hal-00433567

H. Zhang, A. C. Berg, M. Maire, and J. Malik, SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), 2006.
DOI : 10.1109/CVPR.2006.301

J. Zhang, M. Marszalek, S. Lazebnik, and C. Schmid, Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study, International Journal of Computer Vision, vol.36, issue.1, pp.213-238, 2007.
DOI : 10.1007/s11263-006-9794-4

URL : https://hal.archives-ouvertes.fr/inria-00548574