7.10.12 Dynamic Textures

de Knuydt, B., de Smet, S., van Eycken, L.,
Coding of Dynamic Texture for Mapping on 3-D Scenes,
CirSysVideo(9), No. 2, March 1999, pp. 210.
IEEE Top Reference. BibRef 9903

de Knuydt, B.[Bert], de Smet, S.[Stef], van Eycken, L.[Luc], Van Gool, L.J.[Luc J.],
Coding of Dynamic Texture on 3D Scenes,
CAIP99(604-613).
Springer DOI 9909
BibRef

Doretto, G.[Gianfranco], Chiuso, A.[Alessandro], Wu, Y.N.[Ying Nian], Soatto, S.[Stefano],
Dynamic Textures,
IJCV(51), No. 2, February 2003, pp. 91-109.
DOI Link
HTML Version. 0301
BibRef
Earlier: A4, A1, A3 only: ICCV01(II: 439-446).
IEEE DOI 0106
Simple linear models. BibRef

Doretto, G., Soatto, S.,
Editable dynamic textures,
CVPR03(II: 137-142).
IEEE DOI 0307
BibRef
And: Technical ReportUCLA, 020001, January 8, 2002. BibRef
And: SIGGraph-02(xx-yy). BibRef

Doretto, G.[Gianfranco], Jones, E.[Eagle], Soatto, S.[Stefano],
Spatially Homogeneous Dynamic Textures,
ECCV04(Vol II: 591-602).
Springer DOI 0405
BibRef

Saisan, P., Doretto, G., Wu, Y.N., Soatto, S.,
Dynamic Texture Recognition,
CVPR01(II:58-63).
IEEE DOI
PDF File. 0110
BibRef

Doretto, G., Cremers, D., Favaro, P., Soatto, S.,
Dynamic texture segmentation,
ICCV03(1236-1242).
IEEE DOI 0311
BibRef

Peh, C.H., Cheong, L.F.[Loong-Fah],
Synergizing spatial and temporal texture,
IP(11), No. 10, October 2002, pp. 1179-1191.
IEEE DOI 0211
BibRef

Ferrari, R.J., Zhang, H., Kube, C.R.,
Real-time detection of steam in video images,
PR(40), No. 3, March 2007, pp. 1148-1159.
Elsevier DOI 0611
Steam detection; Video segmentation; Detection of dynamic texture; Oil sand BibRef

Bouthemy, P., Hardouin, C., Piriou, G., Yao, J.F.,
Mixed-State Auto-Models and Motion Texture Modeling,
JMIV(25), No. 3, October 2006, pp. 387-402.
Springer DOI 0611
BibRef

Crivelli, T.[Tomas], Cernuschi-Frias, B.[Bruno], Bouthemy, P.[Patrick], Yao, J.F.[Jian-Feng],
Mixed-state causal modeling for statistical KL-based motion texture tracking,
PRL(31), No. 14, 15 October 2010, pp. 2286-2294.
Elsevier DOI 1003
BibRef
Earlier: A1, A3, A2, A4:
Learning mixed-state Markov models for statistical motion texture tracking,
MLMotion09(444-451).
IEEE DOI 0910
Mixed-state Markov models; Motion textures; Visual tracking; Kullback-Leibler divergence BibRef

Mailing, A.[Agustin], Crivelli, T.[Tomás], Cernuschi-Frías, B.[Bruno],
Model Distribution Dependant Complexity Estimation on Textures,
ISVC10(III: 271-279).
Springer DOI 1011
BibRef

Rahman, A.[Ashfaqur], Murshed, M.[Munzitr],
A Temporal Texture Characterization Technique Using Block-Based Approximated Motion Measure,
CirSysVideo(17), No. 10, October 2007, pp. 1370-1382.
IEEE DOI 0711
BibRef
Earlier:
Real-time temporal texture characterisation using block based motion co-occurrence statistics,
ICIP04(III: 1593-1596).
IEEE DOI 0505
BibRef

Rahman, A.[Ashfaqur], Murshed, M.[Munzitr],
Detection of Multiple Dynamic Textures Using Feature Space Mapping,
CirSysVideo(19), No. 5, May 2009, pp. 766-771.
IEEE DOI 0906
BibRef

Rahman, A.[Ashfaqur], Murshed, M.[Manzur],
Multiple temporal texture detection using feature space mapping,
CIVR07(417-424).
DOI Link 0707
BibRef

Chan, A.B.[Antoni B.], Vasconcelos, N.M.[Nuno M.],
Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures,
PAMI(30), No. 5, May 2008, pp. 909-926.
IEEE DOI 0803
BibRef
Earlier:
Classifying Video with Kernel Dynamic Textures,
CVPR07(1-6).
IEEE DOI 0706
BibRef
Earlier:
Mixtures of Dynamic Textures,
ICCV05(I: 641-647).
IEEE DOI 0510
BibRef
And:
Probabilistic Kernels for the Classification of Auto-Regressive Visual Processes,
CVPR05(I: 846-851).
IEEE DOI 0507
Extract textured objects in video. BibRef

Chan, A.B.[Antoni B.], Vasconcelos, N.M.[Nuno M.],
Layered Dynamic Textures,
PAMI(31), No. 10, October 2009, pp. 1862-1879.
IEEE DOI 0909
BibRef
Earlier:
Variational layered dynamic textures,
CVPR09(1062-1069).
IEEE DOI 0906
BibRef

Fazekas, S.[Sándor], Amiaz, T.[Tomer], Chetverikov, D.[Dmitry], Kiryati, N.[Nahum],
Dynamic Texture Detection Based on Motion Analysis,
IJCV(82), No. 1, April 2009, pp. xx-yy.
Springer DOI 0902
BibRef
Earlier: A2, A1, A3, A4:
Detecting Regions of Dynamic Texture,
SSVM07(848-859).
Springer DOI 0705
BibRef

Peteri, R.[Renaud], Fazekas, S.[Sandor], Huiskes, M.J.[Mark J.],
DynTex: A comprehensive database of dynamic textures,
PRL(31), No. 12, 1 September 2010, pp. 1627-1632.
Elsevier DOI 1008
Dynamic texture; Scientific image collections; Video segmentation; Video processing; Pattern recognition; Annotation BibRef

Ravichandran, A.[Avinash], Vidal, R.[René],
Video Registration Using Dynamic Textures,
PAMI(33), No. 1, January 2011, pp. 158-171.
IEEE DOI 1011
BibRef
Earlier: ECCV08(II: 514-526).
Springer DOI 0810
BibRef
Earlier: A2, A1:
Optical Flow Estimation and Segmentation of Multiple Moving Dynamic Textures,
CVPR05(II: 516-521).
IEEE DOI 0507
Spatial and temporal registration of multiple sequences containing, e.g. fireworks, flags, etc. Does not require camera models. BibRef

Ravichandran, A.[Avinash], Chaudhry, R.[Rizwan], Vidal, R.[René],
Categorizing Dynamic Textures Using a Bag of Dynamical Systems,
PAMI(35), No. 2, February 2013, pp. 342-353.
IEEE DOI 1301
BibRef
Earlier:
View-invariant dynamic texture recognition using a bag of dynamical systems,
CVPR09(1651-1657).
IEEE DOI 0906
BibRef

Vidal, R.[Rene], Singaraju, D.[Dheeraj],
A Closed Form Solution to Direct Motion Segmentation,
CVPR05(II: 510-515).
IEEE DOI 0507
BibRef

Ghoreyshi, A.[Atiyeh], Vidal, R.[René],
Segmenting Dynamic Textures with Ising Descriptors, ARX Models and Level Sets,
WDV06(127-141).
Springer DOI 0705
BibRef

Péteri, R.[Renaud],
Tracking dynamic textures using a particle filter driven by intrinsic motion information,
MVA(22), No. 5, September 2011, pp. 781-789.
WWW Link. 1108
BibRef

Chetverikov, D.[Dmitry], Fazekas, S.[Sándor], Haindl, M.[Michal],
Dynamic texture as foreground and background,
MVA(22), No. 5, September 2011, pp. 741-750.
WWW Link. 1108
BibRef

Dubois, S.[Sloven], Péteri, R.[Renaud], Ménard, M.[Michel],
Decomposition of Dynamic Textures Using Morphological Component Analysis,
CirSysVideo(22), No. 2, February 2012, pp. 188-201.
IEEE DOI 1202
BibRef
Earlier:
Decomposition of Dynamic Textures Using Morphological Component Analysis: A New Adaptative Strategy,
ICPR10(2258-2261).
IEEE DOI 1008
BibRef
Earlier:
A Comparison of Wavelet Based Spatio-temporal Decomposition Methods for Dynamic Texture Recognition,
IbPRIA09(314-321).
Springer DOI 0906
BibRef

Ghanem, B.[Bernard], Ahuja, N.[Narendra],
Modeling dynamic swarms,
CVIU(117), No. 1, January 2013, pp. 1-11.
Elsevier DOI 1212
BibRef
Earlier:
Sparse Coding of Linear Dynamical Systems with an Application to Dynamic Texture Recognition,
ICPR10(987-990).
IEEE DOI 1008
BibRef
And:
Maximum Margin Distance Learning for Dynamic Texture Recognition,
ECCV10(II: 223-236).
Springer DOI 1009
BibRef
Earlier:
Extracting a fluid dynamic texture and the background from video,
CVPR08(1-8).
IEEE DOI 0806
BibRef
Earlier:
Phase Based Modelling of Dynamic Textures,
ICCV07(1-8).
IEEE DOI 0710
BibRef
And:
Phase PCA for Dynamic Texture Video Compression,
ICIP07(III: 425-428).
IEEE DOI 0709
Swarms; Dynamic textures; Crowd behavior analysis; Spatiotemporal analysis; Computer vision BibRef

Zhou, B., Zhang, F., Peng, L.,
Compact Representation for Dynamic Texture Video Coding Using Tensor Method,
CirSysVideo(23), No. 2, February 2013, pp. 280-288.
IEEE DOI 1301
BibRef

Mumtaz, A.[Adeel], Coviello, E.[Emanuele], Lanckriet, G.R.G.[Gert R.G.], Chan, A.B.[Antoni B.],
Clustering Dynamic Textures with the Hierarchical EM Algorithm for Modeling Video,
PAMI(35), No. 7, 2013, pp. 1606-1621.
IEEE DOI 1307
BibRef
Earlier: A2, A1, A4, A3:
Growing a bag of systems tree for fast and accurate classification,
CVPR12(1979-1986).
IEEE DOI 1208
BibRef
Earlier: A4, A2, A3, Only:
Clustering dynamic textures with the hierarchical EM algorithm,
CVPR10(2022-2029).
IEEE DOI 1006
Kalman filters; expectation-maximisation algorithm; discrete-time Kalman smoothing filter; video registration BibRef

Mumtaz, A.[Adeel], Coviello, E.[Emanuele], Lanckriet, G.R.G.[Gert R.G.], Chan, A.B.[Antoni B.],
A Scalable and Accurate Descriptor for Dynamic Textures Using Bag of System Trees,
PAMI(37), No. 4, April 2015, pp. 697-712.
IEEE DOI 1503
Clustering algorithms BibRef

Koleini, M.[Mina], Ahmadzadeh, M.R.[Mohammad Reza], Sadri, S.[Saeed],
A new efficient method to characterize dynamic textures based on a two-phase texture and dynamism analysis,
PRL(45), No. 1, 2014, pp. 217-225.
Elsevier DOI 1407
Dictionary of visual words BibRef

Qiao, Y.L.[Yu-Long], Weng, L.X.[Li-Xiang],
Hidden Markov Model Based Dynamic Texture Classification,
SPLetters(22), No. 4, April 2015, pp. 509-512.
IEEE DOI 1411
hidden Markov models BibRef

Xing, Z.Y.[Zheng-Yi], Qiao, Y.L.[Yu-Long], Zhao, Y.[Yue], Liu, W.H.[Wen-Hui],
Dynamic texture classification based on bag-of-models with mixture of student's t-hidden Markov models,
CVIU(230), 2023, pp. 103653.
Elsevier DOI 2303
Dynamic texture classification, Mixture of hidden Markov models, Student's t-distribution, Bag-of-models BibRef

Tiwari, D.[Deepshikha], Tyagi, V.[Vipin],
A novel scheme based on local binary pattern for dynamic texture recognition,
CVIU(150), No. 1, 2016, pp. 58-65.
Elsevier DOI 1608
Dynamic texture BibRef

Wattanachote, K., Shih, T.K.,
Automatic Dynamic Texture Transformation Based on a New Motion Coherence Metric,
CirSysVideo(26), No. 10, October 2016, pp. 1805-1820.
IEEE DOI 1610
Coherence BibRef

Xie, J.[Jin], Fang, Y.[Yi],
Dynamic texture recognition with video set based collaborative representation,
IVC(55, Part 2), No. 1, 2016, pp. 86-92.
Elsevier DOI 1612
Dynamic texture classification BibRef

Wei, X., Li, Y., Shen, H., Chen, F., Kleinsteuber, M., Wang, Z.,
Dynamical Textures Modeling via Joint Video Dictionary Learning,
IP(26), No. 6, June 2017, pp. 2929-2943.
IEEE DOI 1705
Aerodynamics, Computational modeling, Dictionaries, Heuristic algorithms, Sparse matrices, Vehicle dynamics, Dynamic textures modeling, dictionary learning, linear dynamical systems, sparse, representation BibRef

Quan, Y.H.[Yu-Hui], Sun, Y.P.[Yu-Ping], Xu, Y.[Yong],
Spatiotemporal lacunarity spectrum for dynamic texture classification,
CVIU(165), No. 1, 2017, pp. 85-96.
Elsevier DOI 1712
Dynamic textures BibRef

Sagel, A.[Alexander], Kleinsteuber, M.[Martin],
Alignment Distances on Systems of Bags,
CirSysVideo(28), No. 10, October 2018, pp. 2551-2561.
IEEE DOI 1811
Histograms, Visualization, Computational modeling, Kernel, Vehicle dynamics, Mathematical model, Spatiotemporal phenomena, Fréchet mean BibRef

Qiao, Y.L.[Yu-Long], Liu, Q.F.[Qiu-Fei], Liu, W.H.[Wen-Hui],
Dynamic texture classification using Gumbel mixtures in the complex wavelet domain,
IET-IPR(13), No. 1, January 2019, pp. 9-14.
DOI Link 1812
BibRef

Arashloo, S.R.[Shervin Rahimzadeh],
Sparse binarised statistical dynamic features for spatio-temporal texture analysis,
SIViP(13), No. 3, April 2019, pp. 575-582.
WWW Link. 1904
BibRef

Zhao, X., Lin, Y., Liu, L., Heikkilä, J., Zheng, W.,
Dynamic Texture Classification Using Unsupervised 3D Filter Learning and Local Binary Encoding,
MultMed(21), No. 7, July 2019, pp. 1694-1708.
IEEE DOI 1906
Feature extraction, Binary codes, Histograms, Fractals, Encoding, Machine vision, Dynamic texture, local binary pattern BibRef

Amit, Raman, B.[Balasubramanian], Sadhya, D.[Debanjan],
Dynamic texture recognition using local tetra pattern: Three orthogonal planes (LTrP-TOP),
VC(36), No. 3, March 2020, pp. 579-592.
Springer DOI 2002
BibRef

Nguyen, T.T.[Thanh Tuan], Nguyen, T.P.[Thanh Phuong], Bouchara, F.[Frédéric], Nguyen, X.S.[Xuan Son],
Momental directional patterns for dynamic texture recognition,
CVIU(194), 2020, pp. 102882.
Elsevier DOI 2005
Dynamic texture, Dynamic texture recognition, LDP, SBP, LBP, Moment images, Video representation BibRef

Nguyen, T.T.[Thanh Tuan], Nguyen, T.P.[Thanh Phuong], Bouchara, F.[Frédéric],
Directional dense-trajectory-based patterns for dynamic texture recognition,
IET-CV(14), No. 4, June 2020, pp. 162-176.
DOI Link 2005
BibRef

Nguyen, T.T.[Thanh Tuan], Nguyen, T.P.[Thanh Phuong], Bouchara, F.[Frédéric], Nguyen, X.S.[Xuan Son],
Directional Beams of Dense Trajectories for Dynamic Texture Recognition,
ACIVS18(74-86).
Springer DOI 1810
BibRef

Nguyen, T.T.[Thanh Tuan], Nguyen, T.P.[Thanh Phuong], Bouchara, F.[Frédéric],
Dynamic Texture Representation Based on Hierarchical Local Patterns,
ACIVS20(277-289).
Springer DOI 2003
BibRef
Earlier:
Smooth-Invariant Gaussian Features for Dynamic Texture Recognition,
ICIP19(4400-4404)
IEEE DOI 1910
Dynamic Texture, Dynamic Texture Recognition, DoG, Gaussian Filter, LBP, CLBP BibRef

Nguyen, T.T.[Thanh Tuan], Nguyen, T.P.[Thanh Phuong], Bouchara, F.[Frédéric], Vu, N.S.[Ngoc-Son],
Volumes of Blurred-Invariant Gaussians for Dynamic Texture Classification,
CAIP19(I:155-167).
Springer DOI 1909
BibRef

Nguyen, T.T.[Thanh Tuan], Nguyen, T.P.[Thanh Phuong], Bouchara, F.[Frédéric],
Rubik Gaussian-based patterns for dynamic texture classification,
PRL(135), 2020, pp. 180-187.
Elsevier DOI 2006
Dynamic texture, Dynamic texture classification, Gaussian filtering, DoG, LBP, Video representation BibRef

Ghadekar, P.P.[Premanand Pralhad],
Physics-based dynamic texture analysis and synthesis model using GPU,
IET-IPR(14), No. 11, September 2020, pp. 2356-2364.
DOI Link 2009
BibRef

Nguyen, T.T.[Thanh Tuan], Nguyen, T.P.[Thanh Phuong], Bouchara, F.[Frédéric],
Prominent Local Representation for Dynamic Textures Based on High-Order Gaussian-Gradients,
MultMed(23), 2021, pp. 1367-1382.
IEEE DOI 2105
Kernel, Robustness, Videos, Lighting, Encoding, Standards, Dynamic texture, pattern recognition, video representation BibRef

Nguyen, T.T.[Thanh Tuan], Nguyen, T.P.[Thanh Phuong], Bouchara, F.[Frédéric],
A novel filtering kernel based on difference of derivative Gaussians with applications to dynamic texture representation,
SP:IC(98), 2021, pp. 116394.
Elsevier DOI 2109
Dynamic texture, Feature extraction, Gaussian-based filterings, LBP, CLBP, Video representation BibRef

Nguyen, T.T.[Thanh Tuan], Nguyen, T.P.[Thanh Phuong], Bouchara, F.[Frédéric],
Dynamic texture representation based on oriented magnitudes of Gaussian gradients,
JVCIR(81), 2021, pp. 103330.
Elsevier DOI 2112
Dynamic textures, Gaussian-filtered derivatives, Oriented magnitudes, LBP, CLBP, Video representation BibRef

Wang, S.H.[Su-Hong], Jia, C.M.[Chuan-Min], Zhang, X.F.[Xin-Feng], Wang, S.S.[Shan-She], Ma, S.W.[Si-Wei], Gao, W.[Wen],
A Pixel-Level Segmentation-Synthesis Framework for Dynamic Texture Video Compression,
CirSysVideo(32), No. 10, October 2022, pp. 7077-7091.
IEEE DOI 2210
Dynamics, Encoding, Heuristic algorithms, Video compression, Video coding, Visualization, Motion segmentation, video compression BibRef

Nguyen, T.T.[Thanh Tuan], Nguyen, T.P.[Thanh Phuong], Thirion-Moreau, N.[Nadège],
Locating robust patterns based on invariant of LTP-based features,
PRL(165), 2023, pp. 9-16.
Elsevier DOI 2301
Dynamic texture, Local feature extraction, Robust patterns, LTP, CLTP, LBP, CLBP, Video representation BibRef

Sirenden, B.H.[Bernadus Herdi], Mursanto, P.[Petrus], Wijonarko, S.[Sensus],
Dynamic texture analysis using Temporal Gray scale Pattern Image for water surface velocity measurement,
IVC(137), 2023, pp. 104749.
Elsevier DOI 2309
Water surface velocity, Image based measurement, Dynamic texture analysis, Temporal gray-scale pattern image BibRef

Wang, L.L.[Liang-Liang], Zhou, L.[Lei], Liang, P.D.[Pei-Dong], Wang, K.[Ke], Ge, L.Z.[Lian-Zheng],
SMTCNN - A global spatio-temporal texture convolutional neural network for 3D dynamic texture recognition,
IVC(148), 2024, pp. 105145.
Elsevier DOI 2407
Dynamic texture recognition, SMTCNN, Spatio-temporal semantic representation, Deep neural networks BibRef

Nguyen, L.P.[Luong Phat], Mille, J.[Julien], Li, D.H.[Dominique H.], Conte, D.[Donatello], Ragot, N.[Nicolas],
Efficient Dynamic Texture Classification with Probabilistic Motifs,
ICPR22(564-570)
IEEE DOI 2212
Training, Benchmark testing, Probabilistic logic, Encoding, Data mining, Gaussian mixture model BibRef

Bridgeman, L.[Lewis], Guillemaut, J.Y.[Jean-Yves], Hilton, A.[Adrian],
Dynamic Appearance Modelling from Minimal Cameras,
DynaVis21(1760-1769)
IEEE DOI 2109
Computational modeling, Biological system modeling, Cameras, Pattern recognition BibRef

Hadji, I.[Isma], Wildes, R.P.[Richard P.],
A New Large Scale Dynamic Texture Dataset with Application to ConvNet Understanding,
ECCV18(XIV: 334-351).
Springer DOI 1810
BibRef

Katoch, S., Turaga, P., Spanias, A., Tepedelenlioglu, C.,
Fast Non-Linear Methods for Dynamic Texture Prediction,
ICIP18(2107-2111)
IEEE DOI 1809
dynamic textures, phase-space reconstruction, shading prediction, solar energy BibRef

Favorskaya, M.N., Pyataeva, A.V.,
Convolutional Recognition of Dynamic Textures with Preliminary Categorization,
PTVSBB17(47-54).
DOI Link 1805
BibRef

Nguyen, T.T., Nguyen, T.P., Bouchara, F.,
Completed local structure patterns on three orthogonal planes for dynamic texture recognition,
IPTA17(1-6)
IEEE DOI 1804
feature extraction, image capture, image classification, image segmentation, image texture, CLBP, Local structure patterns BibRef

Chubach, O., Garus, P., Wien, M., Ohm, J.R.,
Analysis/synthesis coding of dynamic textures based on motion distribution statistics,
ICIP17(3016-3020)
IEEE DOI 1803
Bit rate, Codecs, Decoding, Dynamics, Encoding, Video compression, Visualization, Dynamic texture coding, motion distribution, texture synthesis BibRef

Zhao, X., Lin, Y., Heikkilä, J.,
Dynamic texture recognition using multiscale PCA-learned filters,
ICIP17(4152-4156)
IEEE DOI 1803
Databases, Dynamics, Electric breakdown, Fractals, Histograms, Principal component analysis, Training, multiscale analysis BibRef

Thakur, U.S., Bhat, M., Bläser, M., Wien, M., Bull, D.R.[David R.], Ohm, J.R.,
Synthesis of fine details in B picture for dynamic textures,
ICIP17(2751-2755)
IEEE DOI 1803
Bit rate, Decoding, Dynamics, Encoding, Image reconstruction, Motion compensation, Video coding, Dynamic Textures, Steerable Pyramids BibRef

Hadji, I., Wildes, R.P.[Richard P.],
A Spatiotemporal Oriented Energy Network for Dynamic Texture Recognition,
ICCV17(3085-3093)
IEEE DOI 1802
feature extraction, image recognition, image representation, image texture, learning (artificial intelligence), neural nets, Visualization BibRef

Shan, S.[Susu], Xu, H., Su, F.,
A new method for spatiotemporal textual saliency detection in video,
ICPR16(3240-3245)
IEEE DOI 1705
Computational modeling, Feature extraction, Image color analysis, Predictive models, Spatiotemporal phenomena, Visualization BibRef

Quan, Y.H.[Yu-Hui], Bao, C.L.[Cheng-Long], Ji, H.[Hui],
Equiangular Kernel Dictionary Learning with Applications to Dynamic Texture Analysis,
CVPR16(308-316)
IEEE DOI 1612
BibRef

Wang, R.Z.[Rui-Zhe], Wei, L.Y.[Ling-Yu], Vouga, E.[Etienne], Huang, Q.X.[Qi-Xing], Ceylan, D.G.[Duy-Gu], Medioni, G.[Gérard], Li, H.[Hao],
Capturing Dynamic Textured Surfaces of Moving Targets,
ECCV16(VII: 271-288).
Springer DOI 1611
BibRef

Naser, K., Ricordel, V., Le Callet, P.,
Modeling the perceptual distortion of dynamic textures and its application in HEVC,
ICIP16(3787-3791)
IEEE DOI 1610
Bit rate BibRef

Nguyen, T.M., Wu, Q.M.J.,
Multi-view dynamic texture learning,
WACV16(1-9)
IEEE DOI 1606
Covariance matrices BibRef

Gunay, O.[Osman], Cetin, A.E.[A. Enis],
Real-time dynamic texture recognition using random sampling and dimension reduction,
ICIP15(3087-3091)
IEEE DOI 1512
Dynamic texture BibRef

Xia, G.S.[Gui-Song], Ferradans, S.[Sira], Peyre, G.[Gabriel], Aujol, J.F.[Jean-Francois],
Compact representations of stationary dynamic textures,
ICIP12(2993-2996).
IEEE DOI 1302
BibRef

Ravichandran, A.[Avinash], Favaro, P.[Paolo], Vidal, R.[René],
A Unified Approach to Segmentation and Categorization of Dynamic Textures,
ACCV10(I: 425-438).
Springer DOI 1011
BibRef

Toreyin, B.U., Dedeoglu, Y., Cetin, A.E., Fazekas, S., Chetverikov, D., Amiaz, T., Kiryati, N.,
Dynamic texture detection, segmentation and analysis,
CIVR07(131-134).
DOI Link 0707
BibRef

Traver, V.J.[V. Javier], Mirmehdi, M.[Majid], Xie, X.H.[Xiang-Hua], Montoliu, R.[Raúl],
Fast Dynamic Texture Detection,
ECCV10(IV: 680-693).
Springer DOI 1009
BibRef

Zhang, J.W.[Jiu-Wen], Sun, X.Q.[Xian-Qiang],
Dynamic Textures Retrieval with Surfacelet Transform,
CISP09(1-5).
IEEE DOI 0910
BibRef

Li, C., Hall, P.M.,
Learning A Stable Structure To Describe Dynamic Texture,
BMVC08(xx-yy).
PDF File. 0809
BibRef

Pashley, H., Hays, J.H., Liu, Y.X.[Yan-Xi],
Motion Texture,
CMU-RI-TR-05-61, September, 2005.
PDF File. BibRef 0509

Hyndman, M., Jepson, A.D., Fleet, D.J.,
Higher-order Autoregressive Models for Dynamic Textures,
BMVC07(xx-yy).
PDF File. 0709
BibRef

Cooper, L.[Lee], Liu, J.[Jun], Huang, K.[Kun],
Spatial Segmentation of Temporal Texture Using Mixture Linear Models,
WDV06(142-150).
Springer DOI 0705
BibRef

Woolfe, F.[Franco], Fitzgibbon, A.W.[Andrew W.],
Shift-Invariant Dynamic Texture Recognition,
ECCV06(II: 549-562).
Springer DOI 0608
BibRef

Lu, Z.Q.[Zong-Qing], Xie, W.X.[Wei-Xin], Pei, J.H.[Ji-Hong], Huang, J.J.[Jian-Jun],
Dynamic Texture Recognition by Spatio-Temporal Multiresolution Histograms,
Motion05(II: 241-246).
IEEE DOI 0502
BibRef

Fujii, M.[Masaharu], Horikoshi, T.[Tsutomu], Otsuka, K.[Kazuhiro], Suzuki, S.[Satoshi],
Feature Extraction of Temporal Texture Based on Spatiotemporal Motion Trajectory,
ICPR98(Vol II: 1047-1051).
IEEE DOI 9808
BibRef

Liu, F.[Fang],
Modeling Spatial and Temporal Textures,
Vismod--462, September 1997. BibRef 9709 Ph.D.Thesis, MIT, 1997.
PS File. BibRef

Szummer, M., Picard, R.W.,
Temporal texture modeling,
ICIP96(III: 823-826).
IEEE DOI 9610
BibRef

Zhu, Z.G.[Zhi-Gang], Xu, G.Y.[Guang-You], Shi, D.J.[Ding-Ji],
Qualitative estimations of range and motion using spatio-temporal textural images,
ICPR94(A:736-738).
IEEE DOI 9410
BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Texture for Defect Detection .