C. Peh and L. F. Cheong, Synergizing spatial and temporal texture, IEEE Trans. IP, vol.11, issue.10, pp.1179-1191, 2002.

P. Saisan, G. Doretto, Y. N. Wu, and S. Soatto, Dynamic texture recognition, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, pp.58-63, 2001.
DOI : 10.1109/CVPR.2001.990925

Y. Wang and S. Hu, Chaotic features for dynamic textures recognition, Soft Computing, vol.6, issue.6, pp.1977-1989, 2016.
DOI : 10.1109/CVPR.2010.5539882

S. R. Arashloo and J. Kittler, Dynamic Texture Recognition Using Multiscale Binarized Statistical Image Features, IEEE Transactions on Multimedia, vol.16, issue.8, pp.2099-2109, 2014.
DOI : 10.1109/TMM.2014.2362855

A. R. Rivera and O. Chae, Spatiotemporal Directional Number Transitional Graph for Dynamic Texture Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.37, issue.10, pp.2146-2152, 2015.
DOI : 10.1109/TPAMI.2015.2392774
URL : https://doi.org/10.1109/tpami.2015.2392774

Y. Xu, Y. Quan, Z. Zhang, H. Ling, and H. Ji, Classifying dynamic textures via spatiotemporal fractal analysis, Pattern Recognition, vol.48, issue.10, pp.3239-3248, 2015.
DOI : 10.1016/j.patcog.2015.04.015

Y. Xu, S. B. Huang, H. Ji, and C. Fermüller, Scale-space texture description on SIFT-like textons, Computer Vision and Image Understanding, vol.116, issue.9, pp.999-1013, 2012.
DOI : 10.1016/j.cviu.2012.05.003

H. Ji, X. Yang, H. Ling, and Y. Xu, Wavelet domain multifractal analysis for static and dynamic texture classification, IEEE Trans. IP, vol.22, issue.1, pp.286-299, 2013.

V. Andrearczyk and P. F. Whelan, Convolutional neural network on three orthogonal planes for dynamic texture classification, Pattern Recognition, vol.76, pp.36-49, 2018.
DOI : 10.1016/j.patcog.2017.10.030

S. R. Arashloo, M. C. Amirani, and A. Noroozi, Dynamic texture representation using a deep multi-scale convolutional network, JVCIR, vol.43, pp.89-97, 2017.

Y. Quan, C. Bao, and H. Ji, Equiangular Kernel Dictionary Learning with Applications to Dynamic Texture Analysis, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.308-316, 2016.
DOI : 10.1109/CVPR.2016.40

Y. Quan, Y. Huang, and H. Ji, Dynamic Texture Recognition via Orthogonal Tensor Dictionary Learning, 2015 IEEE International Conference on Computer Vision (ICCV), pp.73-81, 2015.
DOI : 10.1109/ICCV.2015.17

G. Zhao and M. Pietikäinen, Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.6, pp.915-928, 2007.
DOI : 10.1109/TPAMI.2007.1110

T. T. Nguyen, T. P. Nguyen, and F. Bouchara, Completed local structure patterns on three orthogonal planes for dynamic texture recognition, 2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), pp.1-6, 2017.
DOI : 10.1109/IPTA.2017.8310130
URL : https://hal.archives-ouvertes.fr/hal-01786823

D. Tiwari and V. Tyagi, Dynamic texture recognition based on completed volume local binary pattern, Multidimensional Systems and Signal Processing, vol.21, issue.4, pp.563-575, 2016.
DOI : 10.1109/TIP.2011.2175739

D. Tiwari and V. Tyagi, A novel scheme based on local binary pattern for dynamic texture recognition, Computer Vision and Image Understanding, vol.150, pp.58-65, 2016.
DOI : 10.1016/j.cviu.2016.04.010

D. Tiwari and V. Tyagi, Improved Weber???s law based local binary pattern for dynamic texture recognition, Multimedia Tools and Applications, vol.29, issue.6, pp.6623-6640, 2017.
DOI : 10.1109/TPAMI.2007.1110

D. Tiwari and V. Tyagi, Dynamic texture recognition using multiresolution edge-weighted local structure pattern, Computers & Electrical Engineering, vol.62, pp.485-498, 2017.
DOI : 10.1016/j.compeleceng.2016.11.008

T. Ojala, M. Pietikäinen, and T. Mäenpää, Multiresolution gray-scale and rotation invariant texture classification with local binary patterns, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.7, pp.971-987, 2002.
DOI : 10.1109/TPAMI.2002.1017623

T. P. Nguyen, A. Manzanera, W. G. Kropatsch, and X. S. N-'guyen, Topological Attribute Patterns for texture recognition, Pattern Recognition Letters, vol.80, pp.91-97, 2016.
DOI : 10.1016/j.patrec.2016.06.003
URL : https://hal.archives-ouvertes.fr/hal-01451126

X. Zhao, Y. Lin, and J. Heikkilä, Dynamic Texture Recognition Using Volume Local Binary Count Patterns With an Application to 2D Face Spoofing Detection, IEEE Transactions on Multimedia, vol.20, issue.3, pp.552-566, 2018.
DOI : 10.1109/TMM.2017.2750415

X. S. Nguyen, T. P. Nguyen, F. Charpillet, and N. S. Vu, Local derivative pattern for action recognition in depth images, Multimedia Tools and Applications, vol.29, issue.6, pp.8531-8549, 2018.
DOI : 10.1109/CVPRW.2013.78
URL : https://hal.archives-ouvertes.fr/hal-01657473

B. Zhang, Y. Gao, S. Zhao, and J. Liu, Local derivative pattern versus local binary pattern: Face recognition with high-order local pattern descriptor, IEEE Trans. IP, vol.19, issue.2, pp.533-544, 2010.

X. S. Nguyen, A. I. Mouaddib, T. P. Nguyen, and L. Jeanpierre, Action recognition in depth videos using hierarchical gaussian descriptor, Multimedia Tools and Applications, vol.29, issue.6, 2018.
DOI : 10.1109/CVPRW.2013.78
URL : https://hal.archives-ouvertes.fr/hal-01713003

K. Fan and T. Hung, A novel local pattern descriptor -local vector pattern in highorder derivative space for face recognition, IEEE Trans. IP, vol.23, issue.7, pp.2877-2891, 2014.

H. Wang, A. Kläser, C. Schmid, and C. Liu, Dense Trajectories and Motion Boundary Descriptors for Action Recognition, International Journal of Computer Vision, vol.73, issue.2, pp.60-79, 2013.
DOI : 10.1007/s11263-006-9794-4
URL : https://hal.archives-ouvertes.fr/hal-00725627

T. P. Nguyen, A. Manzanera, M. Garrigues, and N. Vu, SPATIAL MOTION PATTERNS: ACTION MODELS FROM SEMI-DENSE TRAJECTORIES, International Journal of Pattern Recognition and Artificial Intelligence, vol.28, issue.07, 2014.
DOI : 10.1109/TPAMI.2007.1110
URL : https://hal.archives-ouvertes.fr/hal-01118257

R. Fan, K. Chang, C. Hsieh, X. Wang, and C. Lin, LIBLINEAR: A library for large linear classification, Journal of Machine Learning Research, vol.9, pp.1871-1874, 2008.

A. Ravichandran, R. Chaudhry, and R. Vidal, View-invariant dynamic texture recognition using a bag of dynamical systems, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.1651-1657, 2009.
DOI : 10.1109/CVPR.2009.5206847

B. Ghanem and N. Ahuja, Maximum Margin Distance Learning for Dynamic Texture Recognition, LNCS, vol.6312, pp.223-236, 2010.
DOI : 10.1007/978-3-642-15552-9_17

R. Péteri, S. Fazekas, and M. J. Huiskes, DynTex: A comprehensive database of dynamic textures, Pattern Recognition Letters, vol.31, issue.12, pp.1627-1632, 2010.
DOI : 10.1016/j.patrec.2010.05.009

X. Qi, C. G. Li, G. Zhao, X. Hong, and M. Pietikainen, Dynamic texture and scene classification by transferring deep image features, Neurocomputing, vol.171, pp.1230-1241, 2016.
DOI : 10.1016/j.neucom.2015.07.071

J. Ren, X. Jiang, J. Yuan, and G. Wang, Optimizing LBP Structure For Visual Recognition Using Binary Quadratic Programming, IEEE Signal Processing Letters, vol.21, issue.11, pp.1346-1350, 2014.
DOI : 10.1109/LSP.2014.2336252

T. P. Nguyen, N. Vu, and A. Manzanera, Statistical binary patterns for rotational invariant texture classification, Neurocomputing, vol.173, pp.1565-1577, 2016.
DOI : 10.1016/j.neucom.2015.09.029
URL : https://hal.archives-ouvertes.fr/hal-01245103