P. Dollar, V. Rabaud, G. Cottrell, and S. Belongie, Behavior Recognition via Sparse Spatio-Temporal Features, 2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, pp.65-72, 2005.
DOI : 10.1109/VSPETS.2005.1570899

T. Hastie, S. Rosset, J. Zhu, and H. Zou, Multi-class AdaBoost, Statistics and Its Interface, vol.2, issue.3, pp.349-360, 2009.
DOI : 10.4310/SII.2009.v2.n3.a8

I. 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

I. Laptev, M. Marszalek, C. Schmid, and B. Rozenfeld, Learning realistic human actions from movies, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587756

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

M. Raptis and S. Soatto, Tracklet Descriptors for Action Modeling and Video Analysis, Proceedings of the 11th ECCV: Part I, ECCV'10, pp.577-590, 2010.
DOI : 10.1007/978-3-642-15549-9_42

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

D. Sun, S. Roth, and M. J. Black, Secrets of optical flow estimation and their principles, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.2432-2439, 2010.
DOI : 10.1109/CVPR.2010.5539939

M. Vrigkas, V. Karavasilis, C. Nikou, and A. Kakadiaris, Matching mixtures of curves for human action recognition, Computer Vision and Image Understanding, vol.119, issue.0, pp.27-40, 2014.
DOI : 10.1016/j.cviu.2013.11.007

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, M. M. Ullah, A. Kläser, 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

G. Willems, T. Tuytelaars, and L. Gool, An Efficient Dense and Scale-Invariant Spatio-Temporal Interest Point Detector, Proceedings of the 10th ECCV: Part II, ECCV '08, pp.650-663, 2008.
DOI : 10.1007/978-3-540-88688-4_48

J. Zhang, M. Marszalek, S. Lazebnik, and C. Schmid, Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study, CVPR Workshop CVPRW '06. Conference on, pp.13-13, 2006.
DOI : 10.1007/s11263-006-9794-4

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