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

X. Ren and J. Malik, Learning a classification model for segmentation, Proceedings Ninth IEEE International Conference on Computer Vision, 2003.
DOI : 10.1109/ICCV.2003.1238308

B. Leibe, A. Leonardis, and B. Schiele, An Implicit Shape Model for Combined Object Categorization and Segmentation, ECCV workshop on statistical learning in computer vision, 2004.
DOI : 10.1007/11957959_26

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

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

J. Gibert, E. Valveny, and H. Bunke, Graph embedding in vector spaces by node attribute statistics, Pattern Recognition, vol.45, issue.9, pp.3072-3083, 2012.
DOI : 10.1016/j.patcog.2012.01.009

H. Bunke and K. Riesen, Towards the unification of structural and statistical pattern recognition, Pattern Recognition Letters, vol.33, issue.7, pp.811-825, 2012.
DOI : 10.1016/j.patrec.2011.04.017

Y. Boykov, O. Veksler, and R. Zabih, Fast approximate energy minimization via graph cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.11, pp.1222-1239, 2001.
DOI : 10.1109/34.969114
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.112.6806

J. Shi and J. Malik, Normalized cuts and image segmentation, IEEE Trans. Pattern Anal. Mach. Intell. (PAMI), vol.22, issue.8, pp.888-905, 2000.

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
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.4931

T. Tuytelaars, Dense interest points, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.2281-2288, 2010.
DOI : 10.1109/CVPR.2010.5539911

C. Rother, V. Kolmogorov, and A. Blake, "GrabCut", ACM Transactions on Graphics, vol.23, issue.3, pp.309-314, 2004.
DOI : 10.1145/1015706.1015720

T. Cour, S. X. Yu, and J. Shi, Normalized cut segmentation code, 2004.

Y. Boykov and V. Kolmogorov, An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.9, pp.1124-1137, 2004.
DOI : 10.1109/TPAMI.2004.60

V. Kolmogorov and R. Zabih, What energy functions can be minimized via graph cuts?, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.2, pp.147-159, 2004.
DOI : 10.1109/TPAMI.2004.1262177
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.113.1823

Y. Boykov and M. Jolly, Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, 2001.
DOI : 10.1109/ICCV.2001.937505

F. Jou, K. Fan, and Y. Chang, Efficient matching of large-size histograms, Pattern Recognition Letters, vol.25, issue.3, pp.277-286, 2004.
DOI : 10.1016/j.patrec.2003.10.005

L. Fei-fei, R. Fergus, and P. Perona, Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories, Computer Vision and Image Understanding, vol.106, issue.1, 2004.
DOI : 10.1016/j.cviu.2005.09.012

B. Yao and L. Fei-fei, Grouplet: A structured image representation for recognizing human and object interactions, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5540234