H. Azizpour and I. Laptev, Object Detection Using Strongly-Supervised Deformable Part Models, Proc. ECCV, 2012.
DOI : 10.1007/978-3-642-33718-5_60

URL : https://hal.archives-ouvertes.fr/hal-01063338

D. [. Delaitre, I. Fouhey, J. Laptev, A. Sivic, A. Gupta et al., Scene Semantics from Long-Term Observation of People, Proc. ECCV, 2012.
DOI : 10.1007/978-3-642-33783-3_21

URL : https://hal.archives-ouvertes.fr/hal-01060880

J. [. Delaitre, I. Sivic, and . Laptev, Learning person-object interactions for action recognition in still images, Proc. NIPS, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00648156

O. Duchenne, I. Laptev, J. Sivic, F. Bach, and J. Ponce, Automatic annotation of human actions in video, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459279

V. [. Fouhey, A. Delaitre, A. Gupta, I. Efros, J. Laptev et al., People watching: Human actions as a cue for single view geometry, Proc. ECCV, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01060874

E. [. Junejo, I. Dexter, P. Laptev, and . Pérez, Cross-View Action Recognition from Temporal Self-similarities, Proc. ECCV, pages II, pp.293-306, 2008.
DOI : 10.1007/978-3-540-88688-4_22

URL : https://hal.archives-ouvertes.fr/inria-00289708

E. [. Junejo, I. Dexter, P. Laptev, and . Perez, View-Independent Action Recognition from Temporal Self-Similarities, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.1, pp.172-185, 2011.
DOI : 10.1109/TPAMI.2010.68

URL : https://hal.archives-ouvertes.fr/hal-01064695

. [. Laptev, On Space-Time Interest Points, International Journal of Computer Vision, vol.17, issue.8, pp.107-123, 2005.
DOI : 10.1007/s11263-005-1838-7

. [. Laptev, Improvements of Object Detection Using Boosted Histograms, Procedings of the British Machine Vision Conference 2006, pp.949-958, 2006.
DOI : 10.5244/C.20.97

. [. Laptev, Improving object detection with boosted histograms, Image and Vision Computing, vol.27, issue.5, pp.535-544, 2009.
DOI : 10.1016/j.imavis.2008.08.010

S. [. Laptev, P. Belongie, J. Pérez, and . Wills, Periodic motion detection and segmentation via approximate sequence alignment, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.816-823, 2005.
DOI : 10.1109/ICCV.2005.188

B. [. Laptev, C. Caputo, T. Schüldt, and . Lindeberg, Local velocity-adapted motion events for spatio-temporal recognition, Computer Vision and Image Understanding, vol.108, issue.3, pp.207-229, 2007.
DOI : 10.1016/j.cviu.2006.11.023

I. Laptev and T. Lindeberg, Local descriptors for spatio-temporal recognition. In First International Workshop on Spatial Coherence for Visual Motion Analysis, LNCS, vol.3667, pp.91-103, 2004.
DOI : 10.1007/11676959_8

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.78.400

M. [. Laptev, C. Marszaa-lek, B. Schmid, and . Rozenfeld, Learning realistic human actions from movies, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587756

URL : https://hal.archives-ouvertes.fr/inria-00548659

P. [. Laptev and . Pérez, Retrieving actions in movies, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4409105

J. Law-to, L. Chen, A. Joly, I. Laptev, O. Buisson et al., Video copy detection, Proceedings of the 6th ACM international conference on Image and video retrieval, CIVR '07, pp.371-378, 2007.
DOI : 10.1145/1282280.1282336

J. Lezama, K. Alahari, J. Sivic, and I. Laptev, Track to the future: Spatio-temporal video segmentation with long-range motion cues, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.6044588

URL : https://hal.archives-ouvertes.fr/hal-00817961

M. Marszaa-lek, I. Laptev, and C. Schmid, Actions in context, Proc. CVPR, 2009.

M. Rodriguez, I. Laptev, J. Sivic, and J. Audibert, Density-aware person detection and tracking in crowds, 2011 International Conference on Computer Vision, 2011.
DOI : 10.1109/ICCV.2011.6126526

URL : https://hal.archives-ouvertes.fr/hal-00654266

M. Rodriguez, J. Sivic, I. Laptev, and J. Audibert, Data-driven crowd analysis in videos, 2011 International Conference on Computer Vision, 2011.
DOI : 10.1109/ICCV.2011.6126374

URL : https://hal.archives-ouvertes.fr/hal-00654256

C. Schüldt, I. Laptev, and B. Caputo, Recognizing human actions: a local SVM approach, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., pp.32-36, 2004.
DOI : 10.1109/ICPR.2004.1334462

M. M. Ullah, S. N. Parizi, and I. Laptev, Improving bag-of-features action recognition with non-local cues, Procedings of the British Machine Vision Conference 2010, 2010.
DOI : 10.5244/C.24.95

H. Wang, M. M. Ullah, A. Kläser, I. Laptev, and C. Schmid, Evaluation of local spatiotemporal features for action recognition, Proc. BMVC, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00439769

K. Barnard, P. Duygulu, N. De-freitas, D. Forsyth, D. Blei et al., Matching words and pictures, J. Machine Learning Research, 2003.

T. L. Berg, A. C. Berg, J. Edwards, M. Maire, R. White et al., Names and faces in the news, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., 2004.
DOI : 10.1109/CVPR.2004.1315253

I. Biederman, Recognition-by-components: A theory of human image understanding., Psychological Review, vol.94, issue.2, p.115, 1987.
DOI : 10.1037/0033-295X.94.2.115

M. Blank, L. Gorelick, E. Shechtman, M. Irani, and R. Basri, Actions as space-time shapes, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.1395-1402, 2005.
DOI : 10.1109/ICCV.2005.28

O. Boiman and M. Irani, Detecting irregularities in images and in video, Proc. ICCV, pp.462-469, 2005.

P. Buehler, M. Everingham, and A. Zisserman, Learning sign language by watching TV (using weakly aligned subtitles), 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009.
DOI : 10.1109/CVPR.2009.5206523

C. C. Chang and C. J. Lin, LIBSVM, ACM Transactions on Intelligent Systems and Technology, vol.2, issue.3, 2001.
DOI : 10.1145/1961189.1961199

O. Chomat and J. L. Crowley, Probabilistic recognition of activity using local appearance, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149), pp.104-109, 1999.
DOI : 10.1109/CVPR.1999.784616

O. Chum and A. Zisserman, An Exemplar Model for Learning Object Classes, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383050

T. Cour, B. Sapp, C. Jordan, and B. Taskar, Learning from ambiguously labeled images, 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009.
DOI : 10.1109/CVPR.2009.5206667

G. Csurka, C. Dance, L. Fan, J. Willamowski, and C. Bray, Visual categorization with bags of keypoints, Workshop on statistical learning in computer vision, ECCV, 2004.

N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.886-893, 2005.
DOI : 10.1109/CVPR.2005.177

URL : https://hal.archives-ouvertes.fr/inria-00548512

N. Dalal, B. Triggs, and C. Schmid, Human Detection Using Oriented Histograms of Flow and Appearance, Proc. ECCV, pages II, pp.428-441, 2006.
DOI : 10.1023/A:1008162616689

URL : https://hal.archives-ouvertes.fr/inria-00548587

C. Desai, D. Ramanan, and C. Fowlkes, Discriminative models for static human-object interactions, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Workshops, 2010.
DOI : 10.1109/CVPRW.2010.5543176

P. Dollár, V. Rabaud, G. Cottrell, and S. Belongie, Behavior recognition via sparse spatiotemporal features, VS-PETS, 2005.

M. Everingham, J. Sivic, and A. Zisserman, Hello! My name is... Buffy'' -- Automatic Naming of Characters in TV Video, Procedings of the British Machine Vision Conference 2006, 2006.
DOI : 10.5244/C.20.92

M. Everingham, L. Van-gool, C. Williams, and A. Zisserman, The Pascal Visual Object Classes (VOC) Challenge, International Journal of Computer Vision, vol.73, issue.2, 2006.
DOI : 10.1007/s11263-009-0275-4

A. Farhadi, M. Hejrati, A. Sadeghi, P. Young, C. Rashtchian et al., Every Picture Tells a Story: Generating Sentences from Images, Proc. ECCV, 2010.
DOI : 10.1007/978-3-642-15561-1_2

A. Fathi, X. Ren, and J. Rehg, Learning to recognize objects in egocentric activities, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995444

P. Felzenszwalb, R. Girshick, D. Mcallester, and D. Ramanan, Object Detection with Discriminatively Trained Part-Based Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.9, pp.1627-1645, 2010.
DOI : 10.1109/TPAMI.2009.167

P. F. Felzenszwalb and D. P. Huttenlocher, Efficient Graph-Based Image Segmentation, International Journal of Computer Vision, vol.59, issue.2, pp.167-181, 2004.
DOI : 10.1023/B:VISI.0000022288.19776.77

Y. Freund and R. E. Schapire, A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting, Journal of Computer and System Sciences, vol.55, issue.1, pp.119-139, 1997.
DOI : 10.1006/jcss.1997.1504

M. Fritz, B. Leibe, B. Caputo, and B. Schiele, Integrating representative and discriminative models for object category detection, Proc. ICCV, pages II, pp.1363-1370, 2005.
DOI : 10.1109/iccv.2005.124

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.109.6614

A. Gaidon, Z. Harchaoui, and C. Schmid, Temporal Localization of Actions with Actoms, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.11, 2013.
DOI : 10.1109/TPAMI.2013.65

URL : https://hal.archives-ouvertes.fr/hal-00687312

J. Gall, A. Fossati, and L. Van-gool, Functional categorization of objects using real-time markerless motion capture, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995582

J. Gibson, The ecological approach to visual perception, 1979.

M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid, TagProp: Discriminative metric learning in nearest neighbor models for image auto-annotation, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459266

URL : https://hal.archives-ouvertes.fr/inria-00439276

A. Gupta and L. Davis, Beyond Nouns: Exploiting Prepositions and Comparative Adjectives for Learning Visual Classifiers, Proc. ECCV, 2008.
DOI : 10.1007/978-3-540-88682-2_3

A. Gupta, A. Kembhavi, and L. S. Davis, Observing Human-Object Interactions: Using Spatial and Functional Compatibility for Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.10, 2009.
DOI : 10.1109/TPAMI.2009.83

A. Gupta, S. Satkin, A. Efros, and M. Hebert, From 3D scene geometry to human workspace, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995448

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.220.2094

T. Hastie, R. Tibshirani, and J. H. Friedman, The Elements of Statistical Learning, 2003.

V. Hedau, D. Hoiem, and D. Forsyth, Recovering the spatial layout of cluttered rooms, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459411

M. Hein and O. Bousquet, Hilbertian metrics and positive definite kernels on probability measures, Proc. AISTATS, 2005.

D. Hoiem, A. Efros, and M. Hebert, Geometric context from a single image, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005.
DOI : 10.1109/ICCV.2005.107

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.60.6301

B. K. Horn and B. Schunck, Determining optical flow, Artificial Intelligence, vol.17, issue.1-3, pp.185-203, 1981.
DOI : 10.1016/0004-3702(81)90024-2

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.185.1651

A. Howard and T. Jebara, Learning monotonic transformations for classification, Proc. NIPS, 2007.

H. Jhuang, T. Serre, L. Wolf, and T. Poggio, A Biologically Inspired System for Action Recognition, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408988

N. Jojic, A. Perina, and M. Murino, Structural epitome: a way to summarize one's visual experience, Proc. NIPS, pp.1027-1035, 2010.

Y. Ke, R. Sukthankar, and M. Hebert, Efficient visual event detection using volumetric features, Proc. ICCV, pages I, pp.166-173, 2005.

H. Kjellstrom, J. Romero, D. Martinez, and D. Kragic, Simultaneous Visual Recognition of Manipulation Actions and Manipulated Objects, Proc. ECCV, 2008.
DOI : 10.1007/978-3-540-88688-4_25

A. Kläser, M. Marszaa, and C. Schmid, A Spatio-Temporal Descriptor Based on 3D-Gradients, Procedings of the British Machine Vision Conference 2008, 2008.
DOI : 10.5244/C.22.99

A. Kläser, M. Marszaa-lek, C. Schmid, and A. Zisserman, Human Focused Action Localization in Video, International Workshop on Sign, Gesture, and Activity (SGA) in Conjunction with ECCV, 2010.
DOI : 10.1007/978-3-642-35749-7_17

S. Lazebnik, C. Schmid, and J. Ponce, Semi-Local Affine Parts for Object Recognition, Procedings of the British Machine Vision Conference 2004, pp.959-968, 2004.
DOI : 10.5244/C.18.98

URL : https://hal.archives-ouvertes.fr/inria-00548542

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), pp.2169-2178, 2006.
DOI : 10.1109/CVPR.2006.68

URL : https://hal.archives-ouvertes.fr/inria-00548585

J. Liu, B. Kuipers, and S. Savarese, Recognizing human actions by attributes, CVPR 2011, pp.3337-3344, 2011.
DOI : 10.1109/CVPR.2011.5995353

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.463.8447

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

J. Luo, B. Caputo, and V. Ferrari, Who's doing what: Joint modeling of names and verbs for simultaneous face and pose annotation, Proc. NIPS, 2009.

C. Matuszek, E. Herbst, L. Zettlemoyer, and D. Fox, Learning to Parse Natural Language Commands to a Robot Control System, Proc. of the 13th Int'l Symposium on Experimental Robotics (ISER), 2012.
DOI : 10.1007/978-3-319-00065-7_28

K. Mikolajczyk, B. Leibe, and B. Schiele, Local features for object class recognition, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.1792-1799, 2005.
DOI : 10.1109/ICCV.2005.146

A. Ng and M. Jordan, On discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes, Proc. NIPS, 2002.

J. C. Niebles, H. Wang, and L. Fei-fei, Unsupervised learning of human action categories using spatial-temporal words, Proc. BMVC, 2006.

J. C. Niebles, C. Chen, and L. Fei-fei, Modeling Temporal Structure of Decomposable Motion Segments for Activity Classification, Proc. ECCV, pp.392-405, 2010.
DOI : 10.1007/978-3-642-15552-9_29

J. M. Odobez and P. Bouthemy, Robust Multiresolution Estimation of Parametric Motion Models, Journal of Visual Communication and Image Representation, vol.6, issue.4, pp.348-365, 1995.
DOI : 10.1006/jvci.1995.1029

V. Ordonez, G. Kulkarni, and T. L. Berg, Im2text: Describing images using 1 million captioned photographs, Proc. NIPS, 2011.

S. E. Palmer, Vision science: photons to phenomenology, 1999.

F. Perronnin, J. Sánchez, and T. Mensink, Improving the Fisher Kernel for Large-Scale Image Classification, Proc. ECCV, pp.143-156, 2010.
DOI : 10.1007/978-3-642-15561-1_11

URL : https://hal.archives-ouvertes.fr/inria-00548630

P. Peursum, G. West, and S. Venkatesh, Combining image regions and human activity for indirect object recognition in indoor wide-angle views, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005.
DOI : 10.1109/ICCV.2005.57

A. Prest, C. Schmid, and V. Ferrari, Weakly Supervised Learning of Interactions between Humans and Objects, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.3, 2011.
DOI : 10.1109/TPAMI.2011.158

URL : https://hal.archives-ouvertes.fr/inria-00516477

M. Rodriguez, J. Ahmed, and M. Shah, Action MACH a spatio-temporal Maximum Average Correlation Height filter for action recognition, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587727

S. Sadanand and J. J. Corso, Action bank: A high-level representation of activity in video, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.1234-1241, 2012.
DOI : 10.1109/CVPR.2012.6247806

F. Schroff, A. Criminisi, and A. Zisserman, Harvesting image databases from the web, Proc. ICCV, 2007.

F. Sebastiani, Machine learning in automated text categorization, ACM Computing Surveys, vol.34, issue.1, pp.1-47, 2002.
DOI : 10.1145/505282.505283

J. Shawe-taylor and N. Cristianini, Kernel Methods for Pattern Analysis, Camb. U. P, 2004.
DOI : 10.1017/CBO9780511809682

E. Shechtman and M. Irani, Space-Time Behavior Based Correlation, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.405-412, 2005.
DOI : 10.1109/CVPR.2005.328

E. Shechtman and M. Irani, Matching Local Self-Similarities across Images and Videos, 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007.
DOI : 10.1109/CVPR.2007.383198

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.76.1297

J. Sivic, M. Everingham, and A. Zisserman, -learning person specific classifiers from video, Proc. CVPR, 2009.
DOI : 10.1109/cvpr.2009.5206513

URL : https://hal.archives-ouvertes.fr/hal-01110678

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

L. Stark and K. W. Bowyer, Achieving generalized object recognition through reasoning about association of function to structure, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.13, issue.10, pp.1097-1104, 1991.
DOI : 10.1109/34.99242

M. Stark, P. Lies, M. Zillich, J. Wyatt, and B. Schiele, Functional Object Class Detection Based on Learned Affordance Cues, Proc. ICVS, 2008.
DOI : 10.1007/978-3-540-79547-6_42

URL : http://hdl.handle.net/11858/00-001M-0000-0013-C97D-5

K. Tang, L. Fei-fei, and D. Koller, Learning latent temporal structure for complex event detection, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.1250-1257, 2012.
DOI : 10.1109/CVPR.2012.6247808

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.309.7443

M. Turek, A. Hoogs, and R. Collins, Unsupervised Learning of Functional Categories in Video Scenes, Proc. ECCV, 2010.
DOI : 10.1007/978-3-642-15552-9_48

B. Tversky, J. B. Morrison, and J. Zacks, On bodies and events The Imitative Mind, 2002.

P. Viola and M. J. Jones, Robust Real-Time Face Detection, International Journal of Computer Vision, vol.57, issue.2, pp.137-154, 2004.
DOI : 10.1023/B:VISI.0000013087.49260.fb

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.102.9805

H. Wang, A. Kläser, C. Schmid, and C. Liu, Dense trajectories and motion boundary descriptors for action recognition. IJCV, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00725627

X. Wang, K. Tieu, and E. Grimson, Learning Semantic Scene Models by Trajectory Analysis, Proc. ECCV, 2006.
DOI : 10.1007/11744078_9

Y. Wang and G. Mori, A discriminative latent model of image region and object tag correspondence, Proc. NIPS, 2010.

G. Willems, T. Tuytelaars, and L. Vangool, An efficient dense and scale-invariant spatiotemporal interest point detector, Proc. ECCV, 2008.
DOI : 10.1007/978-3-540-88688-4_48

L. Xu, J. Neufeld, B. Larson, and D. Schuurmans, Maximum margin clustering, Proc. NIPS, pp.1537-1544, 2004.

Y. Yang and D. Ramanan, Articulated pose estimation using flexible mixtures of parts, Proc. CVPR, 2011.

B. Yao and L. Fei-fei, Modeling mutual context of object and human pose in human-object interaction activities, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5540235

B. Yao, A. Khosla, and L. Fei-fei, Classifying actions and measuring action similarity by modeling the mutual context of objects and human poses, Proc. ICML, 2011.

L. Zelnik-manor and M. Irani, Event-based analysis of video, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, pp.123-130, 2001.
DOI : 10.1109/CVPR.2001.990935

L. Zelnik-manor and M. Irani, Statistical analysis of dynamic actions, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.9, pp.1530-1535, 2006.
DOI : 10.1109/TPAMI.2006.194

J. Zhang, M. Marszalek, S. Lazebnik, and C. Schmid, Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study, International Journal of Computer Vision, vol.36, issue.1, pp.213-238, 2007.
DOI : 10.1007/s11263-006-9794-4

URL : https://hal.archives-ouvertes.fr/inria-00548574

T. Zhang, Large margin winnow methods for text categorization, KDD-2000 Workshop on Text Mining, 2000.