S. Agarwal, N. Snavely, I. Simon, S. Seitz, and R. Szeliski, Building rome in a day, Proc. ICCV, 2009.

R. Baeza-yates and B. Ribeiro-neto, Modern Information Retrieval, p.20139829, 1999.

D. Blei, A. Ng, and M. Jordan, Latent dirichlet allocation, NIPS, 2002.

A. Bosch, A. Zisserman, and X. Munoz, Scene Classification Using a Hybrid Generative/Discriminative Approach, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.4, 2008.
DOI : 10.1109/TPAMI.2007.70716

L. Cao and L. Fei-fei, Spatially Coherent Latent Topic Model for Concurrent Segmentation and Classification of Objects and Scenes, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408965

C. Chemuduguntu, P. Smyth, and M. Steyvers, Modeling general and specific aspects of documents with a probabilistic topic model, NIPS, 2007.

O. Chum and J. Matas, Web scale image clustering: Large scale discovery of spatially related images, 2008.

O. Chum, J. Matas, and J. Kittler, Locally Optimized RANSAC, In DAGM, pp.236-243, 2003.
DOI : 10.1007/978-3-540-45243-0_31

O. Chum, J. Philbin, M. Isard, and A. Zisserman, Scalable near identical image and shot detection, Proceedings of the 6th ACM international conference on Image and video retrieval, CIVR '07, 2007.
DOI : 10.1145/1282280.1282359

O. Chum, J. Philbin, J. Sivic, M. Isard, and A. Zisserman, Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408891

T. Cormen, C. Leiserson, R. Rivest, and C. Stein, Introduction to Algorithms, 1990.

D. Crandall, L. Backstrom, D. Huttenlocher, and J. Kleinberg, Mapping the world's photos, Proceedings of the 18th international conference on World wide web, WWW '09, 2009.
DOI : 10.1145/1526709.1526812

G. Csurka, C. Bray, C. Dance, and L. Fan, Visual categorization with bags of keypoints, Workshop on Statistical Learning in Computer Vision, ECCV, pp.1-22, 2004.

M. Cummins and P. Newman, Probabilistic Appearance Based Navigation and Loop Closing, Proceedings 2007 IEEE International Conference on Robotics and Automation, 2007.
DOI : 10.1109/ROBOT.2007.363622

L. Fei-fei and P. Perona, A Bayesian Hierarchical Model for Learning Natural Scene Categories, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005.
DOI : 10.1109/CVPR.2005.16

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

M. A. Fischler and R. C. 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. Fritz and B. Schiele, Decomposition, discovery and detection of visual categories using topic models, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587803

T. Griffiths and M. Steyvers, Finding scientific topics, Proceedings of the National Academy of Sciences, pp.5228-5235, 2004.
DOI : 10.1073/pnas.0307752101

T. Hofmann, Unsupervised learning by probabilistic latent semantic analysis, Machine Learning, pp.177-196, 2001.

G. Kim and A. Torralba, Unsupervised detection of regions of interest using iterative link analysis, NIPS, 2009.

L. Li, G. Wang, and L. Fei-fei, Optimol: automatic online picture collection via incremental model learning, Proc. CVPR, 2007.

X. Li, C. Wu, C. Zach, S. Lazebnik, and J. Frahm, Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs, Proc. ECCV, 2008.
DOI : 10.1007/978-3-540-88682-2_33

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

K. Mikolajczyk and C. Schmid, Scale & Affine Invariant Interest Point Detectors, International Journal of Computer Vision, vol.60, issue.1, pp.63-86, 2004.
DOI : 10.1023/B:VISI.0000027790.02288.f2
URL : https://hal.archives-ouvertes.fr/inria-00548554

D. Nister and H. Stewenius, 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

J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman, Object retrieval with large vocabularies and fast spatial matching, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383172

J. Philbin, J. Sivic, and A. Zisserman, Geometric LDA: A Generative Model for Particular Object Discovery, Procedings of the British Machine Vision Conference 2008, 2008.
DOI : 10.5244/C.22.39

J. Philbin and A. Zisserman, Object Mining Using a Matching Graph on Very Large Image Collections, 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing, 2008.
DOI : 10.1109/ICVGIP.2008.103

T. Quack, V. Ferrari, and L. Van-gool, Video Mining with Frequent Itemset Configurations, Proc. CIVR, 2006.
DOI : 10.1007/11788034_37
URL : https://hal.archives-ouvertes.fr/inria-00548580

T. Quack, B. Leibe, and L. Van-gool, World-scale mining of objects and events from community photo collections, Proceedings of the 2008 international conference on Content-based image and video retrieval, CIVR '08, 2008.
DOI : 10.1145/1386352.1386363

P. Quelhas, F. Monay, J. Odobez, D. Gatica, T. Tuytelaars et al., Modeling scenes with local descriptors and latent aspects, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.883-890, 2005.
DOI : 10.1109/ICCV.2005.152

B. C. Russell, A. A. Efros, J. Sivic, W. T. Freeman, and A. Zisserman, Using Multiple Segmentations to Discover Objects and their Extent in Image Collections, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), 2006.
DOI : 10.1109/CVPR.2006.326

F. Schaffalitzky and A. Zisserman, Multi-view Matching for Unordered Image Sets, or ???How Do I Organize My Holiday Snaps????, Proc. ECCV, pp.414-431, 2002.
DOI : 10.1007/3-540-47969-4_28

I. Simon and S. M. Seitz, Scene Segmentation Using the Wisdom of Crowds, Proc. ECCV, 2008.
DOI : 10.1007/978-3-540-88688-4_40

I. Simon, N. Snavely, and S. M. Seitz, Scene Summarization for Online Image Collections, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408863

J. Sivic, B. C. Russell, A. A. Efros, A. Zisserman, and W. T. Freeman, Discovering object categories in image collections, Proc. ICCV, 2005.

J. Sivic, B. C. Russell, A. Zisserman, W. T. Freeman, and A. A. Efros, Unsupervised discovery of visual object class hierarchies, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587622

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. Sivic and A. Zisserman, Video data mining using configurations of viewpoint invariant regions, Proc. CVPR, 2004.

N. Snavely, S. Seitz, and R. Szeliski, Photo tourism: exploring photo collections in 3D, Proc. ACM SIGGRAPH, pp.835-846, 2006.

E. Sudderth, A. Torralba, W. T. Freeman, and A. Willsky, Describing Visual Scenes Using Transformed Objects and Parts, International Journal of Computer Vision, vol.57, issue.2, pp.1-3, 2008.
DOI : 10.1007/s11263-007-0069-5

Z. Tu, X. Chen, A. L. Yuille, and S. C. Zhu, Image parsing: Unifying segmentation, detection, and recognition, IEEE PAMI, vol.62, issue.2, pp.113-140, 2005.

P. Turcot and D. Lowe, Better matching with fewer features: The selection of useful features in large database recognition problems, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, 2009.
DOI : 10.1109/ICCVW.2009.5457541

X. Wang and E. Grimson, Spatial latent dirichlet allocation, NIPS, 2007.

J. Winn and N. Joijic, LOCUS: learning object classes with unsupervised segmentation, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005.
DOI : 10.1109/ICCV.2005.148