H. Aanaes, A. L. Dahl, and K. Pedersen, Interesting Interest Points, International Journal of Computer Vision, vol.59, issue.1, pp.1835-59, 2012.
DOI : 10.1007/s11263-011-0473-8

A. Angeli, D. Filliat, S. Doncieux, and J. Meyer, Fast and Incremental Method for Loop-Closure Detection Using Bags of Visual Words, IEEE Transactions on Robotics, vol.24, issue.5, pp.10271037-10271079, 2008.
DOI : 10.1109/TRO.2008.2004514
URL : https://hal.archives-ouvertes.fr/hal-00652598

S. Avidan, Ensemble tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.2, pp.261271-107, 2007.

R. T. Azuma, A Survey of Augmented Reality, Presence: Teleoperators and Virtual Environments, vol.15, issue.12, p.355385, 1997.
DOI : 10.1109/2945.466720

T. Bailey and H. Durrant-whyte, Simultaneous localization and mapping (SLAM): part II, IEEE Robotics & Automation Magazine, vol.13, issue.3, pp.108117-108154, 2006.
DOI : 10.1109/MRA.2006.1678144

T. Stephen, W. B. Barnard, and . Thompson, Disparity analysis of images, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.2, issue.4, pp.333340-333377, 1980.

H. Bay, A. Ess, T. Tuytelaars, and L. Van-gool, Speeded-up robust features (SURF) Computer Vision and Image Understanding, pp.346359-346400, 2008.

M. Berger, How to track eciently piecewise curved contours with a view to reconstructing 3D objects, ICPR, p.38, 1994.

K. K. Srikrishna-bhat, M. Berger, G. Simon, and F. Sur, Transitive closure based visual words for point matching in video sequence, ICPR, p.49, 2010.

K. K. Srikrishna-bhat, M. Berger, and F. Sur, Visual words for 3D reconstruction and pose computation, 3DIMPVT, p.49, 2011.

T. Botterill, S. Mills, and R. Green, Bag-of-words-driven, single-camera simultaneous localization and mapping, Journal of Field Robotics, vol.25, issue.1, pp.204226-204269, 2011.
DOI : 10.1002/rob.20368

A. J. Bray, Tracking objects using image disparities, Image Vision Computing, vol.8, issue.1, pp.49-86, 1990.

M. Calonder, V. Lepetit, M. Ozuysal, T. Trzinski, C. Strecha et al., BRIEF: Computing a Local Binary Descriptor Very Fast, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.7, pp.12811298-12811335, 2012.
DOI : 10.1109/TPAMI.2011.222

M. A. Carreira-perpinan, Acceleration Strategies for Gaussian Mean-Shift Image Segmentation, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1 (CVPR'06), p.118
DOI : 10.1109/CVPR.2006.44

E. Baptiste-charmette, F. Royer, and . Chausse, Matching planar features for robot localization, International Symposium on Advances in Visual Computing: Part I, p.121, 2009.

Y. Cheng, Mean shift, mode seeking, and clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.17, issue.45, pp.790799-790841, 1995.

D. Comaniciu and P. Meer, Mean shift: a robust approach toward feature space analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.5, pp.603619-603661, 2002.
DOI : 10.1109/34.1000236

G. Csurka, C. R. Dance, L. Fan, J. Willamowski, and C. Bray, Visual categorization with bags of keypoints, Workshop on Statistical Learning in Computer Vision, ECCV, p.46, 2004.

A. Dahl, H. Aanaes, and K. Pedersen, Finding the Best Feature Detector-Descriptor Combination, 2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission, p.36, 2011.
DOI : 10.1109/3DIMPVT.2011.47

A. J. Davison, Real-time simultaneous localisation and mapping with a single camera, Proceedings Ninth IEEE International Conference on Computer Vision, p.39
DOI : 10.1109/ICCV.2003.1238654

A. J. Davison, I. D. Reid, N. D. Molton, and O. Stasse, MonoSLAM: Real-Time Single Camera SLAM, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.6, pp.1052-1067, 2007.
DOI : 10.1109/TPAMI.2007.1049

D. Dementhon, Spatio-temporal segmentation of video by hierarchical mean shift analysis, p.108, 2002.

Z. Dong, G. Zhang, J. Jia, and H. Bao, Efficient keyframe-based real-time camera tracking, ICCV, p.42, 2009.
DOI : 10.1016/j.cviu.2013.08.005

R. Duda, P. Hart, and D. Stork, Pattern classication, pp.45-79, 2001.

M. Fenzi, R. Dragon, L. Leal-taixé, B. Rosenhahn, and J. Ostermann, 3D Object Recognition and Pose Estimation for Multiple Objects Using Multi-Prioritized RANSAC and Model Updating, Pattern Recognition, vol.7476, issue.80, pp.123133-2012
DOI : 10.1007/978-3-642-32717-9_13

A. Martin, R. C. Fischler, and . Bolles, Random sample consensus: a paradigm for model tting with applications to image analysis and automated cartography, Communications of the ACM, vol.24, issue.28, pp.381395-381412, 1981.

W. Forstner, A feature based correspondence algorithm for image matching, ISPRS, p.36, 1986.

D. Freedman and P. Kisilev, Fast Mean Shift by compact density representation, 2009 IEEE Conference on Computer Vision and Pattern Recognition, p.118, 2009.
DOI : 10.1109/CVPR.2009.5206716

K. Fukunaga and L. Hostetler, The estimation of the gradient of a density function, with applications in pattern recognition, IEEE Transactions on Information Theory, vol.21, issue.1, pp.32-40, 1975.
DOI : 10.1109/TIT.1975.1055330

B. Georgescu, I. Shimshoni, and P. Meer, Mean shift based clustering in high dimensions: a texture classification example, Proceedings Ninth IEEE International Conference on Computer Vision, pp.63-108, 2003.
DOI : 10.1109/ICCV.2003.1238382

C. Goad, Readings in computer vision: issues, problems, principles, and paradigms. chapter Special purpose automatic programming for 3D model-based vision, pp.371-381, 1987.

I. Gordon and D. G. Lowe, What and Where: 3D Object Recognition with Accurate Pose, Toward Category-Level Object Recognition, pp.20-42, 2006.
DOI : 10.1007/11957959_4

M. Grabner, H. Grabner, and H. Bischof, Learning Features for Tracking, 2007 IEEE Conference on Computer Vision and Pattern Recognition, p.39, 2007.
DOI : 10.1109/CVPR.2007.382995

W. 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.335-372, 1984.
DOI : 10.1177/027836498400300301

C. Harris and M. Stephens, A Combined Corner and Edge Detector, Procedings of the Alvey Vision Conference 1988, pp.41-43, 1988.
DOI : 10.5244/C.2.23

C. Harris, Tracking with rigid objects, p.38, 1992.

R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, pp.25-32, 2004.
DOI : 10.1017/CBO9780511811685

R. I. Hartley, In defense of the eight-point algorithm, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.19, issue.6, pp.580593-580624, 1997.
DOI : 10.1109/34.601246

J. A. Hesch and S. I. Roumeliotis, A direct least-squares (DLS) solution for PnP, p.34, 2011.

S. Hinterstoisser, V. Lepetit, S. Benhimane, P. Fua, and N. Navab, Learning real-time perspective patch rectication, International Journal of Computer Vision, vol.91, issue.18, pp.107130-107169, 2011.

W. A. Ho, K. Nguyen, and T. Lyon, Computer vision-based registration techniques for augmented reality, Proceedings of Intelligent Robots and Control Systems XV, Intelligent Control Systems and Advanced Manufacturing, p.18, 1996.

J. Hong, X. Tan, B. Pinette, R. Weiss, and E. M. Riseman, Image-based homing, IEEE Control Systems, vol.12, issue.1, pp.3845-3885, 1992.

K. P. Berthold and . Horn, Closed-form solution of absolute orientation using unit quaternions, The Journal of the Optical Society of America A, vol.4, issue.81, pp.629642-629675, 1987.

K. P. Berthold, B. G. Horn, and . Schunck, Determining optical ow, Articial Intelligence, p.38, 1981.

E. Hsiao, A. Collet, and M. Hebert, Making specic features less discriminative to improve point-based 3D object recognition, CVPR, pp.42-46, 2010.

A. Irschara, C. Zach, and H. Bischof, Towards Wiki-based Dense City Modeling, 2007 IEEE 11th International Conference on Computer Vision, p.46, 2007.
DOI : 10.1109/ICCV.2007.4409216

M. Isard and A. Blake, Condensation -conditional density propagation for visual tracking, International Journal of Computer Vision, vol.29, issue.1, pp.528-566, 1998.

H. Jégou, M. Douze, and C. Schmid, On the burstiness of visual elements, 2009 IEEE Conference on Computer Vision and Pattern Recognition, p.48, 2009.
DOI : 10.1109/CVPR.2009.5206609

G. Klein and D. Murray, Parallel Tracking and Mapping for Small AR Workspaces, 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality, p.39, 2007.
DOI : 10.1109/ISMAR.2007.4538852

G. Klein and D. Murray, Full-3D edge tracking with a particle lter, BMVC, p.38, 2006.

D. Koller, G. Klinker, E. Rose, D. Breen, R. Whitaker et al., Real-time vision-based camera tracking for augmented reality applications, Proceedings of the ACM symposium on Virtual reality software and technology , VRST '97, p.18, 1997.
DOI : 10.1145/261135.261152

H. Kollnig and H. Nagel, 3D pose estimation by directly matching polyhedral models to gray value gradients, International Journal of Computer Vision, vol.23, issue.3, pp.283-302, 1997.
DOI : 10.1023/A:1007927317325

J. Leng and H. Wang, Tracking as recognition: a stable 3D tracking framework, ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004., p.40, 2004.
DOI : 10.1109/ICARCV.2004.1469791

V. Lepetit and P. Fua, Monocular Model-Based 3D Tracking of Rigid Objects: A Survey. Foundations and Trends in Computer Graphics and Vision, pp.189-204, 2005.

V. Lepetit and P. Fua, Keypoint recognition using randomized trees, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.9, pp.14651479-14651520, 2006.
DOI : 10.1109/TPAMI.2006.188

V. Lepetit, J. Pilet, and P. Fua, Point Matching as a Classication Problem for Fast and Robust Object Pose Estimation, CVPR, p.41, 2004.

V. Lepetit, F. Moreno-noguer, and P. Fua, EPnP: An Accurate O(n) Solution to the PnP Problem, International Journal of Computer Vision, vol.60, issue.12, pp.155166-155199, 2009.
DOI : 10.1007/s11263-008-0152-6

C. Li, C. Lin, . Bor-chen, H. Kuo, and . Chu, An automatic method for selecting the parameter of the RBF kernel function to support vector machines, 2010 IEEE International Geoscience and Remote Sensing Symposium, pp.98-103, 2010.
DOI : 10.1109/IGARSS.2010.5649251

S. Lieberknecht, S. Benhimane, P. Meier, and N. Navab, A dataset and evaluation methodology for template-based tracking algorithms, 2009 8th IEEE International Symposium on Mixed and Augmented Reality, p.123, 2009.
DOI : 10.1109/ISMAR.2009.5336487

W. Liu, Y. Wang, J. Chen, J. Guo, and Y. Lu, A completely ane invariant image-matching method based on perspective projection, Machine Vision and Applications, pp.231242-122, 2012.

M. I. Lourakis and A. A. Argyros, SBA, ACM Transactions on Mathematical Software, vol.36, issue.1, pp.130-161, 2009.
DOI : 10.1145/1486525.1486527

D. Lowe, Three-dimensional object recognition from single two-dimensional images, Artificial Intelligence, vol.31, issue.3, pp.355395-355432, 1987.
DOI : 10.1016/0004-3702(87)90070-1

G. David and . Lowe, Object recognition from local scale-invariant features, ICCV, pp.41-44, 1999.

D. G. Luenberger, Optimization by vector space methods, p.113, 1969.

J. Luo, A. Pronobis, B. Caputo, and P. Jensfelt, The KTH-IDOL2 Database, KTH Royal Institute of Technology, CVAP/CAS, vol.59, p.80, 2006.

E. Marchand, P. Bouthemy, and F. Chaumette, A 2D???3D model-based approach to real-time visual tracking, Image and Vision Computing, vol.19, issue.13, pp.941955-941993, 2001.
DOI : 10.1016/S0262-8856(01)00054-3
URL : https://hal.archives-ouvertes.fr/inria-00352135

K. Mikolajczyk and J. Matas, Improving Descriptors for Fast Tree Matching by Optimal Linear Projection, 2007 IEEE 11th International Conference on Computer Vision, p.46, 2007.
DOI : 10.1109/ICCV.2007.4408871

K. Mikolajczyk and C. Schmid, A performance evaluation of local descriptors, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.27, issue.10, pp.16151630-16151666, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00548227

K. Mikolajczyk and C. Schmid, An ane invariant interest point detector, ECCV, p.41, 2002.

N. D. Molton, A. J. Davison, and I. D. Reid, Locally Planar Patch Features for Real-Time Structure from Motion, Procedings of the British Machine Vision Conference 2004, p.121, 2004.
DOI : 10.5244/C.18.90

J. Mooser, S. You, and U. Neumann, Real-time object tracking for augmented reality combining graph cuts and optical ow, ISMAR, p.38, 2007.

J. Morel and G. Yu, ASIFT: A New Framework for Fully Affine Invariant Image Comparison, SIAM Journal on Imaging Sciences, vol.2, issue.2, pp.438469-123, 2009.
DOI : 10.1137/080732730

M. David, S. Mount, and . Arya, ANN: A library for approximate nearest neighbor searching, pp.85-117

K. Shree, S. A. Nayar, H. Nene, and . Murase, Real-time 100 object recognition system, ICRA, p.40, 1996.

M. Radford, G. E. Neal, and . Hinton, Learning in graphical models. chapter A view of the EM algorithm that justies incremental, sparse, and other variants, pp.355368-108, 1999.

U. Neumann and S. You, Natural feature tracking for augmented reality, IEEE Transactions on Multimedia, vol.1, issue.1, pp.5364-5402, 1999.
DOI : 10.1109/6046.748171

S. Nicolau, X. Pennec, L. Soler, and N. Ayache, Evaluation of a New 3D/2D Registration Criterion for Liver Radio-Frequencies Guided by Augmented Reality, Proceedings of the International Conference on Surgery simulation and soft tissue modeling, p.92, 2003.
DOI : 10.1007/3-540-45015-7_26
URL : https://hal.archives-ouvertes.fr/inria-00615945

H. Ning, W. Xu, Y. Gong, and T. Huang, Discriminative learning of visual words for 3D human pose estimation, CVPR, p.46, 2008.

D. Nister, An ecient solution to the ve-point relative pose problem, CVPR, p.30, 2003.

D. Nister, O. Naroditsky, and J. Bergen, Visual odometry, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., p.39, 2004.
DOI : 10.1109/CVPR.2004.1315094

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), pp.42-44, 2006.
DOI : 10.1109/CVPR.2006.264

E. Nuutila, Ecient transitive closure computation in large digraphs Acta Polytechnica Scandinavia: Mathematics and computing in engineering series, pp.1124-52, 1995.

M. Ozuysal, M. Calonder, V. Lepetit, and P. Fua, Fast Keypoint Recognition Using Random Ferns, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.3, pp.448461-448498, 2010.
DOI : 10.1109/TPAMI.2009.23

M. Ozuysal, V. Lepetit, F. Fleuret, and P. Fua, Feature Harvesting for Tracking-by-Detection, ECCV, p.44, 2006.
DOI : 10.1007/11744078_46

P. S. Sastry, Computing and information sciences: Recent trend. chapter An introduction to support vector machines, p.98, 2002.

E. Rosten and T. Drummond, Machine Learning for High-Speed Corner Detection, ECCV, p.36, 2006.
DOI : 10.1007/11744023_34

F. Rothganger, S. Lazebnik, C. Schmid, and J. Ponce, 3D object modeling and recognition using local ane-invariant image descriptors and multi-view spatial constraints, International Journal of Computer Vision, vol.66, issue.3, pp.231259-231300, 2006.

E. Royer, M. Lhuillier, D. Michel, and J. Lavest, Monocular Vision for Mobile Robot Localization and Autonomous Navigation, International Journal of Computer Vision, vol.32, issue.1, pp.237260-237303, 2007.
DOI : 10.1007/s11263-006-0023-y

E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, ORB: An ecient alternative to SIFT or SURF, ICCV 2011, p.37

F. Schaalitzky and A. Zisserman, Automated location matching in movies, Computer Vision and Image Understanding, vol.92, pp.236264-236312, 2003.

G. Schindler, M. Brown, and R. Szeliski, City-Scale Location Recognition, 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.17-44, 2007.
DOI : 10.1109/CVPR.2007.383150

J. Shi and C. Tomasi, Good features to track, CVPR, p.39, 1994.

R. Sim, G. Dudek-]-r, G. Sim, G. Dudek, M. Simon et al., Mobile robot localization from learned landmarks Learning visual landmarks for pose estimation A two-stage robust statistical method for temporal registration from features of various type, International Conference on Intelligent Robots and Systems ICRA ICCV, pp.40-40, 1998.

G. Simon and M. Berger, Pose estimation for planar structures, IEEE Computer Graphics and Applications, vol.22, issue.6, pp.4653-4692, 2002.
DOI : 10.1109/MCG.2002.1046628
URL : https://hal.archives-ouvertes.fr/inria-00100802

G. Simon, A. W. Fitzgibbon, and A. Zisserman, Markerless tracking using planar structures in the scene, Proceedings IEEE and ACM International Symposium on Augmented Reality (ISAR 2000), p.37, 2000.
DOI : 10.1109/ISAR.2000.880935
URL : https://hal.archives-ouvertes.fr/inria-00099115

G. Simon, V. Lepetit, and M. Berger, Computer vision methods for registration: mixing 3D knowledge and 2d correspondences for accurate image composition, Proceedings of the international workshop on Augmented reality : placing articial objects in real scenes, pp.111127-106, 1999.

J. Sivic and A. Zisserman, Video Google: a text retrieval approach to object matching in videos, Proceedings Ninth IEEE International Conference on Computer Vision, p.44
DOI : 10.1109/ICCV.2003.1238663

N. Snavely, S. M. Seitz, and R. Szeliski, Photo tourism: exploring photo collections in 3D, ACM SIGGRAPH, p.25, 2006.

C. Strecha, A. M. Bronstein, M. M. Bronstein, and P. Fua, LDAHash: Improved Matching with Smaller Descriptors, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.1, pp.6678-6714, 2012.
DOI : 10.1109/TPAMI.2011.103

M. Tamaazousti, V. Gay-bellile, S. N. Collette, S. Bourgeois, and M. Dhome, Nonlinear renement of structure from motion reconstruction by taking advantage of a partial knowledge of the environment, CVPR, p.44, 2011.

P. H. Torr and A. Zisserman, MLESAC: A New Robust Estimator with Application to Estimating Image Geometry, Computer Vision and Image Understanding, vol.78, issue.1, pp.138156-92, 2000.
DOI : 10.1006/cviu.1999.0832

M. Trajkovic and M. Hedley, Fast corner detection, Image and Vision Computing, vol.16, issue.2, pp.7587-7626, 1998.
DOI : 10.1016/S0262-8856(97)00056-5

L. Vacchetti, V. Lepetit, and P. Fua, Stable real-time 3D tracking using online and offline information, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.10, pp.1385-1391, 2004.
DOI : 10.1109/TPAMI.2004.92

J. Valls-miro, W. Zhou, and G. Dissanayake, Towards vision based navigation in large indoor environments, International Conference on Intelligent Robots and Systems, p.39, 2006.

J. C. Van-gemert, C. J. Veenman, A. W. Smeulders, and J. Geusebroek, Visual Word Ambiguity, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.7, pp.1271-1283, 2010.
DOI : 10.1109/TPAMI.2009.132

A. Vedaldi and B. Fulkerson, Vlfeat, Proceedings of the international conference on Multimedia, MM '10, p.63
DOI : 10.1145/1873951.1874249

P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, p.40, 2001.
DOI : 10.1109/CVPR.2001.990517

P. Wang, D. Lee, A. G. Gray, and J. M. Rehg, Fast mean shift with accurate and stable convergence, Journal of Machine Learning Research -Proceedings Track, vol.2, pp.604611-108, 2007.

C. Xiao and M. Liu, Ecient Mean-shift Clustering Using Gaussian KD-Tree, Computer Graphics Forum, vol.29, issue.7, pp.20652073-108

J. Xiao, J. Chen, D. Yeung, and L. Quan, Structuring Visual Words in 3D for Arbitrary-View Object Localization, ECCV, p.42, 2008.
DOI : 10.1007/978-3-540-88690-7_54

C. Yang, R. Duraiswami, N. A. Gumerov, and L. Davis, Improved fast gauss transform and ecient kernel density estimation, ICCV 2003, p.107

X. Yuan, B. Hu, and R. He, Agglomerative Mean-Shift Clustering via Query Set Compression, Proceedings of the SIAM International Conference on Data Mining, p.118, 2009.
DOI : 10.1137/1.9781611972795.20