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.

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.

S. R. Arashloo and J. Kittler, Dynamic texture recognition using multiscale binarized statistical image features, IEEE Trans. Multimedia, vol.16, issue.8, pp.2099-2109, 2014.
DOI : 10.1109/tmm.2014.2362855

S. Dubois, R. Péteri, and M. Ménard, Characterization and recognition of dynamic textures based on the 2d+t curvelet transform, SIVP, vol.9, issue.4, pp.819-830, 2015.

R. Fan, K. Chang, C. Hsieh, X. Wang, and C. Lin, LIBLIN-EAR: A library for large linear classification, JMLR, vol.9, pp.1871-1874, 2008.

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

Z. Guo, L. Zhang, and D. Zhang, A completed modeling of local binary pattern operator for texture classification, IEEE Trans. IP, vol.19, issue.6, pp.1657-1663, 2010.

S. Hong, J. Ryu, W. Im, and H. S. Yang, D3: recognizing dynamic scenes with deep dual descriptor based on key frames and key segments, Neurocomputing, vol.273, pp.611-621, 2018.
DOI : 10.1016/j.neucom.2017.08.046

T. Mäenpää and M. Pietikäinen, Multi-scale binary patterns for texture analysis, SCIA, pp.885-892, 2003.

T. P. Nguyen, A. Manzanera, W. G. Kropatsch, and X. S. N'guyen, Topological attribute patterns for texture recognition, Pattern Recogn Lett, vol.80, pp.91-97, 2016.
DOI : 10.1016/j.patrec.2016.06.003

URL : https://hal.archives-ouvertes.fr/hal-01451126

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

T. T. Nguyen, T. P. Nguyen, and F. Bouchara, Completed local structure patterns on three orthogonal planes for dynamic texture recognition, IPTA, pp.1-6, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01786823

T. T. Nguyen, T. P. Nguyen, and F. Bouchara, Completed statistical adaptive patterns on three orthogonal planes for recognition of dynamic textures and scenes, J. Electronic Imaging, vol.27, issue.05, p.53044, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01978443

T. T. Nguyen, T. P. Nguyen, F. Bouchara, and X. S. Nguyen, Directional beams of dense trajectories for dynamic texture recognition, ACIVS, pp.74-86, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01860067

T. Ojala, M. Pietikäinen, and T. Mäenpää, Multiresolution gray-scale and rotation invariant texture classification with local binary patterns, IEEE Trans. PAMI, vol.24, issue.7, pp.971-987, 2002.
DOI : 10.1109/tpami.2002.1017623

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

R. Péteri, S. Fazekas, and M. J. Huiskes, Dyntex: A comprehensive database of dynamic textures, Pattern Recogn Lett, vol.31, issue.12, pp.1627-1632, 2010.

X. Qi, C. 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

URL : http://arxiv.org/pdf/1502.00303

Y. Quan, C. Bao, and H. Ji, Equiangular kernel dictionary learning with applications to dynamic texture analysis, 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, ICCV, pp.73-81, 2015.
DOI : 10.1109/iccv.2015.17

Y. Quan, Y. Sun, and Y. Xu, Spatiotemporal lacunarity spectrum for dynamic texture classification, vol.165, pp.85-96, 2017.

J. Ren, X. Jiang, and J. Yuan, Dynamic texture recognition using enhanced LBP features, ICASSP, pp.2400-2404, 2013.

J. Ren, X. Jiang, J. Yuan, and G. Wang, Optimizing LBP structure for visual recognition using binary quadratic programming, SPL, vol.21, issue.11, pp.1346-1350, 2014.

A. R. Rivera and O. Chae, Spatiotemporal directional number transitional graph for dynamic texture recognition, IEEE Trans. PAMI, vol.37, issue.10, pp.2146-2152, 2015.

P. Saisan, G. Doretto, Y. N. Wu, and S. Soatto, Dynamic texture recognition, CVPR, pp.58-63, 2001.

D. Tiwari and V. Tyagi, Dynamic texture recognition based on completed volume local binary pattern, MSSP, vol.27, issue.2, pp.563-575, 2016.

D. Tiwari and V. Tyagi, A novel scheme based on local binary pattern for dynamic texture recognition, vol.150, pp.58-65, 2016.

D. Tiwari and V. Tyagi, Dynamic texture recognition using multiresolution edge-weighted local structure pattern, Comput Electr Eng, vol.62, pp.485-498, 2017.

D. Tiwari and V. Tyagi, Improved weber's law based local binary pattern for dynamic texture recognition, Multimedia Tools Appl, vol.76, issue.5, pp.6623-6640, 2017.

Y. Wang and S. Hu, Chaotic features for dynamic textures recognition, Soft Computing, vol.20, issue.5, pp.1977-1989, 2016.

Y. Xu, S. B. Huang, H. Ji, and C. Fermüller, Scale-space texture description on sift-like textons, CVIU, vol.116, issue.9, pp.999-1013, 2012.

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.

G. Zhao and M. Pietikäinen, Dynamic texture recognition using local binary patterns with an application to facial expressions, IEEE Trans. PAMI, vol.29, issue.6, pp.915-928, 2007.

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 Trans. Multimedia, vol.20, issue.3, pp.552-566, 2018.

Y. Zhao, D. Huang, and W. Jia, Completed Local Binary Count for Rotation Invariant Texture Classification, IEEE Trans. IP, vol.21, issue.10, pp.4492-4497, 2012.