J. K. Aggarwal and Q. Cai, Human motion analysis: a review, 1999.

M. Ahad, J. Tan, H. Kim, and S. Ishikawa, Motion History Image, 2010.
DOI : 10.1007/978-1-4471-4730-5_3

P. Banerjee and R. Nevatia, Learning neighborhood cooccurrence statistics of sparse features for human activity recognition, 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2011.
DOI : 10.1109/AVSS.2011.6027324

Y. Benabbas, A. Lablack, N. Ihaddadene, and C. Djeraba, Action Recognition Using Direction Models of Motion, 2010 20th International Conference on Pattern Recognition, 2010.
DOI : 10.1109/ICPR.2010.1044

URL : https://hal.archives-ouvertes.fr/hal-00730582

J. Davis, Hierarchical motion history images for recognizing human motion, Proceedings IEEE Workshop on Detection and Recognition of Events in Video, 2001.
DOI : 10.1109/EVENT.2001.938864

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, 2005.
DOI : 10.1109/VSPETS.2005.1570899

C. Galleguillos and S. Belongie, Context based object categorization: A critical survey, Computer Vision and Image Understanding, vol.114, issue.6, 2010.
DOI : 10.1016/j.cviu.2010.02.004

URL : http://authors.library.caltech.edu/18786/1/Galleguillos2010p10445Computer_Vision_And_Image_Understanding.pdf

A. Gilbert, J. Illingworth, and R. Bowden, Fast realistic multi-action recognition using mined dense spatio-temporal features, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459335

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.158.3113

A. Gupta and L. S. Davis, Objects in Action: An Approach for Combining Action Understanding and Object Perception, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383331

Z. Jiang, Z. Lin, and L. Davis, Recognizing human actions by learning and matching shape-motion prototype trees, 2011.

M. Kaaniche and F. Bremond, Gesture recognition by learning local motion signatures, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010.
DOI : 10.1109/CVPR.2010.5539999

URL : https://hal.archives-ouvertes.fr/inria-00486110

T. Kim, S. Wong, and R. Cipolla, Tensor Canonical Correlation Analysis for Action Classification, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383137

T. Kim and Z. Uddin, Silhouette-based Human Activity Recognition Using Independent Component Analysis, Linear Discriminant Analysis and Hidden Markov Model, InTech, 2010.
DOI : 10.5772/7614

A. Klaser, M. Marszalek, and C. Schmid, A spatio-temporal descriptor based on 3d-gradients Learning a hierarchy of discriminative space-time neighborhood features for human action recognition, BMVC CVPR, 2008.

I. Laptev, On space-time interest points, IJCV, 2005.

I. Laptev, M. Marszalek, 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

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), 2006.
DOI : 10.1109/CVPR.2006.68

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

L. Li and L. Fei-fei, What, where and who? Classifying events by scene and object recognition, 2007 IEEE 11th International Conference on Computer Vision, 2007.
DOI : 10.1109/ICCV.2007.4408872

Z. Lin, Z. Jiang, and L. S. Davis, Recognizing actions by shape-motion prototype trees, ICCV, 2009.

J. Liu, J. Luo, and M. Shah, Recognizing realistic actions from videos " in the wild, CVPR, 2009.

J. Liu and M. Shah, Learning human action via information maximization, CVPR, 2008.

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

P. Matikainen, M. Hebert, and R. Sukthankar, Representing Pairwise Spatial and Temporal Relations for Action Recognition, ECCV, 2010.
DOI : 10.1007/978-3-642-15549-9_37

R. Messing, C. Pal, and H. Kautz, Activity recognition using the velocity histories of tracked keypoints, 2009 IEEE 12th International Conference on Computer Vision, 2009.
DOI : 10.1109/ICCV.2009.5459154

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

K. Rapantzikos, Y. Avrithis, and S. Kollias, Dense saliencybased spatiotemporal feature points for action recognition, CVPR, 2009.

M. Raptis and S. Soatto, Tracklet Descriptors for Action Modeling and Video Analysis, ECCV, 2010.
DOI : 10.1007/978-3-642-15549-9_42

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.178.8838

S. Satkin and M. Hebert, Modeling the Temporal Extent of Actions, ECCV, 2010.
DOI : 10.1007/978-3-642-15549-9_39

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

J. Sun, X. Wu, S. Yan, L. Cheong, T. Chua et al., Hierarchical spatio-temporal context modeling for action recognition, CVPR, 2009.

H. Wang, A. Klaser, C. Schmid, and L. Cheng-lin, Action recognition by dense trajectories, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995407

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

H. Wang, M. M. Ullah, A. Klaser, 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

J. Wang, Z. Chen, and Y. Wu, Action recognition with multiscale spatio-temporal contexts, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995493

G. Willems, T. Tuytelaars, and L. Gool, An Efficient Dense and Scale-Invariant Spatio-Temporal Interest Point Detector, ECCV, 2008.
DOI : 10.1007/978-3-540-88688-4_48

S. Wu, O. Oreifej, and M. Shah, Action recognition in videos acquired by a moving camera using motion decomposition of Lagrangian particle trajectories, 2011 International Conference on Computer Vision, 2011.
DOI : 10.1109/ICCV.2011.6126397

X. Wu, D. Xu, L. Duan, and J. Luo, Action recognition using context and appearance distribution features, CVPR 2011, 2011.
DOI : 10.1109/CVPR.2011.5995624