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, Proceedings of the ICML Workshop on Text Learning, 2002. ,
Visual categorizationwith bags of keypoints, ECCV workshop on Statistical Learning in ComputerVision, pp.59-74, 2004. ,
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
Pascal visual object classes challenge results, 2005. ,
DOI : 10.1007/11736790_8
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.101.6521
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
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.114.7863
Computer vision: A modern approach, 2003. ,
URL : https://hal.archives-ouvertes.fr/hal-01063327
Invariant statistics and coding of natural microimages, IEEE Workshop on Statistical and Computational Theories of Vision, 1999. ,
Mean shift based clustering in high dimensions: A texture classification example Detection du visage par caracteristiques generiques calculees a partir des images de luminance, ICCV Reconnaissance des Formes et Intelligence Artificiel, pp.456-463, 2003. ,
The Elements of Statistical Learning: Data Mining, Inference , and Prediction, 2001. ,
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
Text categorization with Support Vector Machines: Learning with many relevant features, Tenth European Conference on Machine Learning ECML-98, pp.137-142, 1999. ,
DOI : 10.1007/BFb0026683
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
Creating efficient codebooks for visual recognition, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005. ,
DOI : 10.1109/ICCV.2005.66
URL : https://hal.archives-ouvertes.fr/inria-00548511
Interleaved Object Categorization and Segmentation, Procedings of the British Machine Vision Conference 2003, 2003. ,
DOI : 10.5244/C.17.78
Representing and recognizing the visual appearance of materials using threedimensional 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
The online median problem, FOCS '00: Proceedings of the 41st Annual Symposium on Foundations of Computer Science, p.339, 2000. ,
An Affine Invariant Interest Point Detector, ECCV, 2002. ,
DOI : 10.1007/3-540-47969-4_9
URL : https://hal.archives-ouvertes.fr/inria-00548252
A performance evaluation of local descriptors, pp.257-263, 2003. ,
URL : https://hal.archives-ouvertes.fr/inria-00548227
The nature of statistical learning theory, 1995. ,
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
Mining with rarity: a unifying framework, SIGKDD Explor. Newsl, vol.6, issue.1, pp.7-19, 2004. ,
What are textons? IJCV, pp.121-143, 2005. ,