Learning to detect objects in images via a sparse, part-based representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.11, pp.1475-1490, 2004. ,
DOI : 10.1109/TPAMI.2004.108
Interaction of feature selection methods and linear classification models, ICML'02 Workshop on Text Learning, 2002. ,
Mean shift: a robust approach toward feature space analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.5, pp.603-619, 2002. ,
DOI : 10.1109/34.1000236
Visual categorization with bags of keypoints, ECCV'04 workshop on Statistical Learning in Computer Vision, pp.59-74, 2004. ,
Scatter/gather: A cluster-based approach to browsing large document collections, SIGR, pp.318-329, 1992. ,
Selection of scale-invariant parts for object class recognition, Proceedings Ninth IEEE International Conference on Computer Vision, pp.634-640, 2003. ,
DOI : 10.1109/ICCV.2003.1238407
URL : https://hal.archives-ouvertes.fr/inria-00548234
A Multiple Resampling Method for Learning from Imbalanced Data Sets, Computational Intelligence, vol.19, issue.3, pp.18-36, 2004. ,
DOI : 10.1109/78.668782
Object class recognition by unsupervised scale-invariant learning, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., pp.264-271, 2003. ,
DOI : 10.1109/CVPR.2003.1211479
Invariant statistics and coding of natural microimages Mean shift based clustering in high dimensions: a texture classification example, IEEE Workshop on Statistical and Computational Theories of Vision ICCV, pp.456-463, 1999. ,
Face recognition: component-based versus global approaches, Computer Vision and Image Understanding, vol.91, issue.1-2, pp.6-21, 2003. ,
DOI : 10.1016/S1077-3142(03)00073-0
Textons, the elements of texture perception, and their interactions, Nature, vol.32, issue.5802, pp.91-97, 1981. ,
DOI : 10.1038/290091a0
Scale-invariant shape features for recognition of object categories, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., pp.90-96, 2004. ,
DOI : 10.1109/CVPR.2004.1315149
URL : https://hal.archives-ouvertes.fr/inria-00548545
A sparse texture representation using local affine regions, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.27, issue.8, pp.1265-1278, 2005. ,
DOI : 10.1109/TPAMI.2005.151
URL : https://hal.archives-ouvertes.fr/inria-00548530
Occlusion models for natural images: A statistical study of a scale-invariant dead leaves model, International Journal of Computer Vision, vol.41, issue.1/2, pp.35-59, 2001. ,
DOI : 10.1023/A:1011109015675
Interleaved Object Categorization and Segmentation, Procedings of the British Machine Vision Conference 2003, 2003. ,
DOI : 10.5244/C.17.78
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.103.3586
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
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
Online facility location, Proceedings 2001 IEEE International Conference on Cluster Computing, pp.426-433, 2001. ,
DOI : 10.1109/SFCS.2001.959917
A k-Median Algorithm with Running Time Independent of Data Size, Machine Learning, pp.1-361, 2004. ,
DOI : 10.1023/B:MACH.0000033115.78247.f0
An Affine Invariant Interest Point Detector, ECCV, p.128, 2002. ,
DOI : 10.1007/3-540-47969-4_9
URL : https://hal.archives-ouvertes.fr/inria-00548252
Milic-Frayling. Feature selection using linear classifier weights: Interaction with classification models, SIGIR, pp.234-241, 2004. ,
Sharing features: efficient boosting procedures for multiclass object detection, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., pp.762-769, 2004. ,
DOI : 10.1109/CVPR.2004.1315241
Object recognition with informative features and linear classification, Proceedings Ninth IEEE International Conference on Computer Vision, pp.281-288, 2003. ,
DOI : 10.1109/ICCV.2003.1238356
Unsupervised Learning of Models for Recognition, ECCV, pages I, pp.18-32, 2000. ,
DOI : 10.1007/3-540-45054-8_2
Categorizing nine visual classes using local appearance descriptors, Workshop on Learning for Adaptable Visual Systems (LAVS04), 2004. ,
What are textons? IJCV, pp.121-143, 2005. ,
DOI : 10.1007/3-540-47979-1_53
Selected Studies of the Principle of Relative Frequency in Language, 1932. ,