J. Aggarwal and L. Xia, Human activity recognition from 3D data: A review, Pattern Recognition Letters, vol.48, 2014.
DOI : 10.1016/j.patrec.2014.04.011

A. Alwani, A. Chahir, and Y. , 3-d skeleton joints-based action recognition using covariance descriptors on discrete spherical harmonics transform, International Conference on Image Processing (ICIP) 2015, IEEE, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01168436

M. Alnowami, B. Alnwaimi, F. Tahavori, M. Copland, and K. Wells, A quantitative assessment of using the Kinect for Xbox360 for respiratory surface motion tracking, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, pp.1-10, 2012.
DOI : 10.1117/12.911463

A. A. Alwani, Y. Chahir, D. E. Goumidi, M. Molina, and F. Jouen, 3D-Posture Recognition Using Joint Angle Representation, Information Processing and Management of Uncertainty in Knowledge-Based Systems -15th International Conference Proceedings, Part II, pp.106-115, 2014.
DOI : 10.1007/978-3-319-08855-6_12
URL : https://hal.archives-ouvertes.fr/hal-01168442

W. V. Antnio, L. Thomas, S. William, and F. M. Mario, Distance matrices as invariant features for classifying mocap data, ICPR 2012 (21st International Conference on Pattern Recognition), IEEE, pp.2934-2937, 2012.

M. Barnachon, S. Bouakaz, B. Boufama, and E. Guillou, A real-time system for motion retrieval and interpretation, Pattern Recognition Letters, vol.34, issue.15, 2013.
DOI : 10.1016/j.patrec.2012.12.020
URL : https://hal.archives-ouvertes.fr/hal-01339146

V. Bloom, D. Makris, and V. Argyriou, G3D: A gaming action dataset and real time action recognition evaluation framework, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp.7-12, 2012.
DOI : 10.1109/CVPRW.2012.6239175

B. Bustos, D. A. Keim, D. Saupe, T. Schreck, and D. V. Vrani, Feature-based similarity search in 3D object databases, ACM Computing Surveys, vol.37, issue.4, pp.345-387, 2005.
DOI : 10.1145/1118890.1118893

C. C. Chang and C. J. Lin, LIBSVM, ACM Transactions on Intelligent Systems and Technology, vol.2, issue.3, pp.1-27, 2011.
DOI : 10.1145/1961189.1961199

X. Chen and M. Koskela, Skeleton-based action recognition with extreme learning machines, Neurocomputing, vol.149, p.10
DOI : 10.1016/j.neucom.2013.10.046

M. Devanne, H. Wannous, S. Berretti, P. Pala, M. Daoudi et al., Space-Time Pose Representation for 3D Human Action Recognition, pp.456-464, 2013.
DOI : 10.1007/978-3-642-41190-8_49
URL : https://hal.archives-ouvertes.fr/hal-00839494

G. Evangelidis, G. Singh, and R. Horaud, Skeletal Quads: Human Action Recognition Using Joint Quadruples, 2014 22nd International Conference on Pattern Recognition, pp.4513-4518, 2014.
DOI : 10.1109/ICPR.2014.772
URL : https://hal.archives-ouvertes.fr/hal-00989725

W. Freeden and S. Michael, Spherical Functions of Mathematical Geosciences: A Scalar, Vectorial, and Tensorial Setup, 2009.

G. B. Huang, H. Zhou, X. Ding, and R. Zhang, Extreme Learning Machine for Regression and Multiclass Classification, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol.42, issue.2, pp.513-529, 2012.
DOI : 10.1109/TSMCB.2011.2168604

G. B. Huang, Q. Y. Zhu, and C. K. Siew, Extreme learning machine: Theory and applications, Neurocomputing, vol.70, issue.1-3, pp.489-501, 2006.
DOI : 10.1016/j.neucom.2005.12.126

M. E. Hussein, M. Torki, M. A. Gowayyed, and M. El-saban, Human action recognition using a temporal hierarchy of covariance descriptors on 3d joint locations, Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, pp.2466-2472, 2013.

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), p.21692178, 2006.
DOI : 10.1109/CVPR.2006.68
URL : https://hal.archives-ouvertes.fr/inria-00548585

W. Li, Z. Zhang, and Z. Liu, Action recognition based on a bag of 3D points, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Workshops, pp.9-14, 2010.
DOI : 10.1109/CVPRW.2010.5543273

F. Lv and R. Nevatia, Recognition and Segmentation of 3-D Human Action Using HMM and Multi-class AdaBoost, Proceedings of the 9th European Conference on Computer Vision -Volume Part IV, pp.359-372, 2006.
DOI : 10.1109/CVPR.2005.58

R. Minhas, A. Baradarani, S. Seifzadeh, and W. Q. Jonathan, Human action recognition using extreme learning machine based on visual vocabularies, Neurocomputing, vol.73, issue.10-12, pp.1906-1917, 2010.
DOI : 10.1016/j.neucom.2010.01.020

M. Muller, Information Retrieval for Music and Motion
DOI : 10.1007/978-3-540-74048-3

S. Obdrzalek, G. Kurillo, F. Ofli, R. Bajcsy, E. Seto et al., Accuracy and robustness of Kinect pose estimation in the context of coaching of elderly population, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.1188-1193, 2012.
DOI : 10.1109/EMBC.2012.6346149

O. Bar, E. Trivedi, and M. , Joint angles similarities and hog2 for action recognition, pp.465-470, 2013.

M. Raptis, D. Kirovski, and H. Hoppe, Real-time classification of dance gestures from skeleton animation, Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, SCA '11, pp.147-156, 2011.
DOI : 10.1145/2019406.2019426

M. Raptis, K. Wnuk, and S. Soatto, Flexible dictionaries for action classification , in: The 1st International Workshop on Machine Learning for Visionbased Motion Analysis -MLVMA'08, 2008.

V. Raviteja, A. Felipe, and C. Rama, Human action recognition by representing 3d skeletons as points in a lie group, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

L. Seidenari, V. Varano, S. Berretti, D. Bimbo, A. Pala et al., Recognizing Actions from Depth Cameras as Weakly Aligned Multi-part Bag-of-Poses, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.479-485, 2013.
DOI : 10.1109/CVPRW.2013.77

A. Shimada and R. I. Taniguchi, Gesture recognition using sparse code of Hierarchical SOM, 2008 19th International Conference on Pattern Recognition, pp.1-4, 2008.
DOI : 10.1109/ICPR.2008.4761795

J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio et al., Real-time human pose recognition in parts from a single depth image

R. A. Silverman, Special Functions and their Applications, 1972.

D. Vranic, An improvement of rotation invariant 3d-shape descriptor based on functions on concentric spheres, ICIP03, IEEE, pp.757-760, 2003.

J. Wang, Z. Liu, Y. Wu, and J. Yuan, Mining actionlet ensemble for action recognition with depth cameras, 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.1290-1297, 2012.
DOI : 10.1109/CVPR.2012.6247813

J. Y. Wang and H. M. Lee, Recognition of Human Actions Using Motion Capture Data and Support Vector Machine, 2009 WRI World Congress on Software Engineering, pp.234-238, 2009.
DOI : 10.1109/WCSE.2009.354

L. Xia, C. C. Chen, and J. K. Aggarwal, View invariant human action recognition using histograms of 3D joints, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp.20-27, 2012.
DOI : 10.1109/CVPRW.2012.6239233

X. Yang and Y. Tian, Eigenjoints-based action recognition using navebayes-nearest-neighbor ., in: CVPR Workshops, pp.14-19, 2012.

A. Yao, J. Gall, G. Fanelli, and L. V. Gool, Does Human Action Recognition Benefit from Pose Estimation?, Procedings of the British Machine Vision Conference 2011, 2011.
DOI : 10.5244/C.25.67

M. Ye, Q. Zhang, L. W. Zhu, J. Yang, R. Gall et al., A survey on human motion analysis from depth data Time-of-Flight and Depth Imaging, pp.149-187, 2013.

L. Zhang and D. Samaras, Face recognition from a single training image under arbitrary unknown lighting using spherical harmonics, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.3, pp.351-363, 2006.
DOI : 10.1109/TPAMI.2006.53

X. Zhao, X. Li, C. Pang, and S. Wang, Human action recognition based on semi-supervised discriminant analysis with global constraint, Neurocomputing, vol.105, 2013.
DOI : 10.1016/j.neucom.2012.04.038

Y. Zhu, W. Chen, and G. Guo, Fusing Spatiotemporal Features and Joints for 3D Action Recognition, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.486-491, 2013.
DOI : 10.1109/CVPRW.2013.78