I. Laptev, M. Marsza?ek, C. Schmid, and B. 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

J. Carlos-niebles, H. Wang, and L. Fei-fei, Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words, International Journal of Computer Vision, vol.25, issue.25, pp.299-318, 2008.
DOI : 10.1007/s11263-007-0122-4

M. Marszalek, I. Laptev, and C. Schmid, Actions in context, 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009.
DOI : 10.1109/CVPR.2009.5206557

URL : https://hal.archives-ouvertes.fr/inria-00548645

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

R. Emonet, J. Varadarajan, and J. Odobez, Extracting and locating temporal motifs in video scenes using a hierarchical non parametric Bayesian model, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995572

T. B. Moeslund, A. Hilton, and V. Kruger, A survey of advances in vision-based human motion capture and analysis, Computer Vision and Image Understanding, vol.104, issue.2-3, pp.90-126, 2006.
DOI : 10.1016/j.cviu.2006.08.002

R. Poppe, A survey on vision-based human action recognition, Image and Vision Computing, vol.28, issue.6, pp.976-990, 2010.
DOI : 10.1016/j.imavis.2009.11.014

B. Yao and L. Fei-fei, Action Recognition with Exemplar Based 2.5D Graph Matching, European Conference on Computer Vision, 2012.
DOI : 10.1007/978-3-642-33765-9_13

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

H. Wang, A. Kläser, C. Schmid, and C. Liu, Action recognition by dense trajectories, CVPR 2011, pp.3169-3176, 2011.
DOI : 10.1109/CVPR.2011.5995407

URL : https://hal.archives-ouvertes.fr/inria-00583818

I. Laptev and T. Lindeberg, Space-time interest points, International Conference on Computer Vision, pp.432-439, 2003.
DOI : 10.1109/iccv.2003.1238378

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.4.4359

J. Yamato, J. Ohya, and K. Ishii, Recognizing human action in time-sequential images using hidden Markov model, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.379-385, 1992.
DOI : 10.1109/CVPR.1992.223161

C. Sminchisescu, A. Kanaujia, Z. Li, and D. Metaxas, Conditional models for contextual human motion recognition, International Conference on Computer Vision, pp.1808-1815, 2005.

P. F. Felzenszwalb, R. B. 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

T. Hofmann, Unsupervised Learning by Probabilistic Latent Semantic Analysis, Machine Learning, pp.177-196, 2001.

M. David, A. Y. Blei, M. I. Ng, and . Jordan, Latent dirichlet allocation, Journal of Machine Learning Research, vol.3, pp.993-1022, 2003.

X. Wang, X. Ma, and W. E. Grimson, Unsupervised Activity Perception in Crowded and Complicated Scenes Using Hierarchical Bayesian Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.3, pp.539-555, 2009.
DOI : 10.1109/TPAMI.2008.87

T. Huynh, M. Fritz, and B. Schiele, Discovery of activity patterns using topic models, Proceedings of the 10th international conference on Ubiquitous computing, UbiComp '08, pp.10-19, 2008.
DOI : 10.1145/1409635.1409638

K. Farrahi and D. G. Perez, What did you do today?, Proceeding of the 16th ACM international conference on Multimedia, MM '08, pp.849-852, 2008.
DOI : 10.1145/1459359.1459503

S. Lacoste-julien, F. Sha, and M. I. Jordan, DiscLDA: Discriminative learning for dimensionality reduction and classification, Advances in Neural Information Processing Systems, 2008.

D. M. Blei and J. D. Mcauliffe, Supervised topic models, Advances in Neural Information Processing Systems, pp.121-128, 2008.

M. David, J. D. Blei, and . Lafferty, Dynamic topic models, International conference on Machine learning, pp.113-120, 2006.

X. Wang, A. Mccallum, and X. Wei, Topical ngrams: Phrase and topic discovery, with an application to information retrieval, IEEE International Conference on Data Mining, 2007.

T. Hospedales, S. Gong, and T. Xiang, A markov clustering topic model for mining behavior in video, International Conference on Computer Vision, 2009.

T. Faruquie, P. Kalra, and S. Banerjee, Time based Activity Inference using Latent Dirichlet Allocation, Procedings of the British Machine Vision Conference 2009, 2009.
DOI : 10.5244/C.23.70

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.645.4612

J. Varadarajan, R. Emonet, and J. Odobez, Probabilistic Latent Sequential Motifs: Discovering Temporal Activity Patterns in Video Scenes., Procedings of the British Machine Vision Conference 2010, 2010.
DOI : 10.5244/C.24.117

J. Li, S. Gong, and T. Xiang, Discovering multi-camera behaviour correlations for on-the-fly global activity prediction and anomaly detection, IEEE International Workshop on Visual Surveillance, 2009.

A. Krithara, M. R. Amini, J. M. Renders, and C. Goutte, Semisupervised document classification with a mislabeling error model, Proceedingsof the European Conference on Information Retrieval, 2008.
DOI : 10.1007/978-3-540-78646-7_34

URL : https://hal.archives-ouvertes.fr/hal-01301551

C. Schuldt, 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

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.173.6790

L. Gorelick, M. Blank, E. Shechtman, M. Irani, and R. Basri, Actions as Space-Time Shapes, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.12, pp.2247-2253, 2007.
DOI : 10.1109/TPAMI.2007.70711

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