T. Cao, X. Wu, J. Guo, S. Yu, and Y. Xu, Abnormal crowd motion analysis, 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp.1709-1714, 2009.
DOI : 10.1109/ROBIO.2009.5420408

X. Cao, H. Zhang, C. Deng, Q. Liu, and H. Liu, Action recognition using 3D DAISY descriptor, Machine Vision and Applications, vol.73, issue.2, pp.159-171, 2014.
DOI : 10.1007/s11263-006-9794-4

C. Chang and C. Lin, LIBSVM, ACM Transactions on Intelligent Systems and Technology, vol.2, issue.3, pp.1-2727, 2011.
DOI : 10.1145/1961189.1961199

R. Chaudhry, A. Ravichandran, G. Hager, and R. Vidal, Histograms of oriented optical flow and binetcauchy kernels on nonlinear dynamical systems for the recognition of human actions, Computer Vision and Pattern Recognition CVPR 2009. IEEE Conference on, pp.1932-1939, 2009.

A. Efros, A. C. Berg, G. Mori, M. , and J. , Recognizing action at a distance, Proceedings Ninth IEEE International Conference on Computer Vision, 2003.
DOI : 10.1109/ICCV.2003.1238420
URL : http://lear.inrialpes.fr/people/triggs/events/iccv03/cdrom/iccv03/0726_efros.pdf

M. Garrigues and A. Manzanera, Real Time Semi-dense Point Tracking, Int. Conf. on Image Analysis and Recognition, pp.245-252, 2012.
DOI : 10.1007/978-3-642-31295-3_29
URL : https://hal.archives-ouvertes.fr/hal-01118324

N. Ikizler, R. Cinbis, and P. Duygulu, Human action recognition with line and flow histograms, 2008 19th International Conference on Pattern Recognition, pp.1-4, 2008.
DOI : 10.1109/ICPR.2008.4761434
URL : http://www.cs.bilkent.edu.tr/~duygulu/papers/ICPR2008-ActionLine.pdf

M. Jain, H. Jegou, and P. Bouthemy, Better Exploiting Motion for Better Action Recognition, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.2555-2562, 2013.
DOI : 10.1109/CVPR.2013.330
URL : https://hal.archives-ouvertes.fr/hal-00813014

V. Kantorov and I. Laptev, Efficient feature extraction , encoding and classification for action recog- nition, 2014.
DOI : 10.1109/cvpr.2014.332

Y. Ke, R. Sukthankar, and M. Hebert, Efficient visual event detection using volumetric features, Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on, pp.166-173, 2005.

I. Laptev, M. Marsza?ek, C. Schmid, R. , and B. , 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. Liu, J. Luo, and M. Shah, Recognizing realistic actions from videos " in the wild, IEEE International Conference on Computer Vision and Pattern Recogni- tion, 2009.

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://www.nada.kth.se/%7Ecaputo/publik/icpr04actions.pdf

P. Scovanner, S. Ali, and M. Shah, A 3-dimensional sift descriptor and its application to action recognition, Proceedings of the 15th international conference on Multimedia , MULTIMEDIA '07, pp.357-360, 2007.
DOI : 10.1145/1291233.1291311

H. Tabia, M. Gouiffes, and L. Lacassagne, Motion histogram quantification for human action recognition, Pattern Recognition (ICPR), 2012 21st International Conference on, pp.2404-2407, 2012.

H. Wang, A. Klaser, 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

H. Wang and C. Schmid, Action Recognition with Improved Trajectories, 2013 IEEE International Conference on Computer Vision, pp.3551-3558, 2013.
DOI : 10.1109/ICCV.2013.441
URL : https://hal.archives-ouvertes.fr/hal-00873267

H. Wang, M. M. Ullah, A. Kliser, I. Laptev, and C. Schmid, Evaluation of local spatio-temporal features for action recognition, Procedings of the British Machine Vision Conference 2009, 2009.
DOI : 10.5244/C.23.124
URL : https://hal.archives-ouvertes.fr/inria-00439769

D. Weinland, R. Ronfard, and E. Boyer, A survey of vision-based methods for action representation, segmentation and recognition, Computer Vision and Image Understanding, vol.115, issue.2, pp.224-241, 2011.
DOI : 10.1016/j.cviu.2010.10.002
URL : https://hal.archives-ouvertes.fr/hal-00640088

G. Willems, T. Tuytelaars, and L. Gool, An Efficient Dense and Scale-Invariant Spatio-Temporal Interest Point Detector, Proceedings of the 10th European Conference on Computer Vision: Part II, ECCV '08, pp.650-663, 2008.
DOI : 10.1109/ICCV.2007.4409049

T. Yu, T. Kim, and R. Cipolla, Real-time Action Recognition by Spatiotemporal Semantic and Structural Forests, Procedings of the British Machine Vision Conference 2010, 2010.
DOI : 10.5244/C.24.52

Z. Zhang, Y. Hu, S. Chan, C. , and L. , Motion Context: A New Representation for Human Action Recognition, Computer Vision?ECCV, pp.817-829, 2008.
DOI : 10.1007/978-3-540-88693-8_60