Y. Boureau, F. Bach, Y. L. Cun, 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

L. Breiman, Random forests, Machine Learning, vol.45, issue.1, pp.5-32, 2001.
DOI : 10.1023/A:1010933404324

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

B. Fulkerson, A. Vedaldi, and S. Soatto, Localizing Objects with Smart Dictionaries, ECCV, 2008.
DOI : 10.1007/978-3-540-88682-2_15

P. Geurts, D. Ernst, and L. Wehenkel, Extremely randomized trees, Machine Learning, pp.3-42, 2006.
DOI : 10.1007/s10994-006-6226-1
URL : https://hal.archives-ouvertes.fr/hal-00341932

T. Joachims, A support vector method for multivariate performance measures, Proceedings of the 22nd international conference on Machine learning , ICML '05, 2005.
DOI : 10.1145/1102351.1102399

F. Jurie and B. Triggs, Creating efficient codebooks for visual recognition, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.604-610, 2005.
DOI : 10.1109/ICCV.2005.66
URL : https://hal.archives-ouvertes.fr/inria-00548511

J. Kelley, The cutting-plane method for solving convex programs, SIAM Journal on Control and Optimization, 1960.

J. Krapac, J. Verbeek, and F. Jurie, Modeling spatial layout with fisher vectors for image categorization, 2011 International Conference on Computer Vision, 2011.
DOI : 10.1109/ICCV.2011.6126406
URL : https://hal.archives-ouvertes.fr/inria-00612277

S. Lazebnik and M. Raginsky, Supervised learning of quantizer codebooks by information loss minimization. Pattern Analysis and Machine Intelligence, pp.1294-1309, 2009.

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

B. Leibe, K. Mikolajczyk, and B. Schiele, Efficient Clustering and Matching for Object Class Recognition, Procedings of the British Machine Vision Conference 2006, 2006.
DOI : 10.5244/C.20.81

T. Leung and J. Malik, Representing and recognizing the visual appearance of materials using three-dimensional textons, International Journal of Computer Vision, vol.43, issue.1, pp.29-44, 2001.
DOI : 10.1023/A:1011126920638

X. Lian, Z. Li, B. Lu, and L. Zhang, Max-Margin Dictionary Learning for Multiclass Image Categorization, ECCV, 2010.
DOI : 10.1007/978-3-642-15561-1_12

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

J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman, Supervised dictionary learning, NIPS, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00322431

S. Maji, A. Berg, . Krapac, J. Verbeek, . Trees et al., Max-margin additive models for detection Randomized clustering forests for image classification, ICCV, pp.1632-1646, 2008.

D. Nistér and H. Stewénius, Scalable Recognition with a Vocabulary Tree, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), 2006.
DOI : 10.1109/CVPR.2006.264

E. Nowak, F. Jurie, and B. Triggs, Sampling Strategies for Bag-of-Features Image Classification, ECCV, 2006.
DOI : 10.1007/11744085_38
URL : https://hal.archives-ouvertes.fr/hal-00203752

A. Opelt and A. Pinz, Object Localization with Boosting and Weak Supervision for Generic Object Recognition, SCIA, 2005.
DOI : 10.1007/11499145_87

F. Perronnin, Universal and adapted vocabularies for generic visual categorization. Pattern Analysis and Machine Intelligence, pp.1243-1256, 2008.

F. Perronnin, J. Sánchez, and Y. Liu, Large-scale image categorization with explicit data embedding, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5539914

J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman, Lost in quantization: Improving particular object retrieval in large scale image databases, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587635

M. Roizman and M. Last, Look-Ahead Mechanism Integration in Decision Tree Induction Models, Advances in Web Intelligence and Data Mining, 2006.
DOI : 10.1007/3-540-33880-2_29

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

J. Van-gemert, C. Veenman, A. Smeulders, and J. Geusebroek, Visual word ambiguity . Pattern Analysis and Machine Intelligence, pp.1271-1283, 2010.

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

J. Winn, A. Criminisi, and T. Minka, Object categorization by learned universal visual dictionary, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005.
DOI : 10.1109/ICCV.2005.171
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.93.8714

J. Yang, K. Yu, and T. Huang, Supervised translation-invariant sparse coding, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5539958
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.206.339

L. Yang, R. Jin, R. Sukthankar, and F. Jurie, Unifying discriminative visual codebook generation with classifier training for object category recognition, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587504
URL : https://hal.archives-ouvertes.fr/inria-00548653

J. Zhang, M. Marsza?ek, 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

W. Zhang, A. Surve, X. Fern, and T. Dietterich, Learning non-redundant codebooks for classifying complex objects, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, 2009.
DOI : 10.1145/1553374.1553533