Dynamic texture analysis and segmentation using deterministic partially self-Avoiding walks

Expert Systems with Applications

Volumn 40, Issue 11, 2013, Pages 4283-4300

  Gonçalves, Wesley Nunes ^a   Bruno, Odemir Martinez ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

Deterministic partially self Avoiding walks; Dynamic texture; Dynamic texture recognition

Indexed keywords

DYNAMIC TEXTURE RECOGNITION; DYNAMIC TEXTURES; ORTHOGONAL PLANE; SELF AVOIDING WALK; SELF-SIMILARITIES; SPATIO-TEMPORAL DOMAINS; TEXTURE ANALYSIS; VISION COMMUNITIES;

INFORMATION SYSTEMS; MATHEMATICAL MODELS;

TEXTURES;

EID: 84876066854     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2012.12.092     Document Type: Article

References (33)

1. A.R. Backes, W.N. Gonçalves, A.S. Martinez, and O.M. Bruno Texture analysis and classification using deterministic tourist walk Pattern Recognition 43 3 2010 685 694
2. A.R. Backes, A.S. Martinez, and O.M. Bruno Texture analysis based on maximum contrast walker Pattern Recognition Letters 31 12 2010 1701 1707 10.1016/j.patrec.2010.05.022
3. A.R. Backes, A.S. Martinez, and O.M. Bruno Texture analysis using graphs generated by deterministic partially self-Avoiding walks Pattern Recognition 44 8 2011 1684 1689
4. L. Barrington, A.B. Chan, and G. Lanckriet Modeling music as a dynamic texture Transactions on Audio Speech and Language Processing 18 3 2010 602 612
5. Brieu, N., Serbanovic-Canic, J., Stemple, D., Ouwehand, W., Navab, N., & Groher, M. (2009). A dynamic texture approach to semi-Automatic thrombosis segmentation in in-vivo microscopic video-sequences. In Microcopic image analysis and application in biology (MIAAB). Bethesda, MD, United States.
6. Brieu, N., Serbanovic-Canic, J., Cvejic, A., Stemple, D., Ouwehand, W., Navab, N., & Groher, M. (2010). Thrombus segmentation by texture dynamics from microscopic image sequences. In Progress in biomedical optics and imaging-Proceedings of SPIE (Vol. 7623). http://dx.doi.org/10.1117/12.844230.
7. Chan, A. B., & Vasconcelos, N. (2005). Classification and retrieval of traffic video using auto-regressive stochastic processes. In IEEE intelligent vehicles symposium (pp. 771-776).
8. Chan, A. B., & Vasconcelos, N. (2007). Classifying video with kernel dynamic textures. IEEE Computer society conference on computer vision and pattern recognition (pp. 1-6).
9. A.B. Chan, and N. Vasconcelos Modeling, clustering, and segmenting video with mixtures of dynamic textures IEEE Transactions on Pattern Analysis and Machine Intelligence 30 5 2008 909 926
10. A.B. Chan, and N. Vasconcelos Layered dynamic textures IEEE Transactions on Pattern Analysis and Machine Intelligence 31 10 2009 1862 1879
11. D. Chetverikov, and R. Péteri A brief survey of dynamic texture description and recognition Proceedings of the 4th international conference on computer recognition systems Advances in soft computing Vol. 30 2005 Springer 17 26
12. de la Torre, F., & Black, M. (2001). Robust principal component analysis for computer vision. In ICCV01 (Vol. I, pp. 362-369).
13. P. Dollar, V. Rabaud, G. Cottrell, and S. Belongie Behavior recognition via sparse spatio-temporal features ICCCN '05: Proceedings of the 14th international conference on computer communications and networks 2005 IEEE Computer Society Washington, DC, USA 65 72
14. G. Doretto, A. Chiuso, Y.N. Wu, and S. Soatto Dynamic textures International Journal of Computer Vision 51 2 2003 91 109
15. Doretto, G., Cremers, D., Favaro, P., & Soatto, S. (2003). Dynamic texture segmentation. In ICCV (pp. 1236-1242).
16. S. Dubois, R. Péteri, and M. Ménard A comparison of wavelet based spatio-temporal decomposition methods for dynamic texture recognition IbPRIA '09: Proceedings of the 4th Iberian conference on pattern recognition and image analysis 2009 Springer-Verlag Berlin, Heidelberg 314 321
17. R. Fablet, and P. Bouthemy Motion recognition using nonparametric image motion models estimated from temporal and multiscale cooccurrence statistics IEEE Transactions on Pattern Analysis and Machine Intelligence 25 12 2003 1619 1624
18. S. Fazekas, T. Amiaz, D. Chetverikov, and N. Kiryati Dynamic texture detection based on motion analysis International Journal of Computer Vision 82 2009 48 63 10.1007/s11263-008-0184-y
19. S. Fazekas, and D. Chetverikov Analysis and performance evaluation of optical flow features for dynamic texture recognition SP:IC 22 7-8 2007 680 691
20. Fujii, M., Horikoshi, T., Otsuka, K., & Suzuki, S. (1998). Feature extraction of temporal texture based on spatiotemporal motion trajectory. In ICPR (Vol. II, pp. 1047-1051).
21. Ghoreyshi, A., & Vidal, R. (2006). Segmenting dynamic textures with Ising descriptors, arx models and level sets. In Dynamical vision workshop in the European conference on computer vision (pp. 127-141).
22. Gonçalves, W. N., Machado, B. B., & Bruno, O. M. Spatiotemporal gabor filters: A new method for dynamic texture recognition. Available at: .
23. Gonçalves, W.G., Backes, A. R., Martinez, A. S., & Bruno, O.M. (2012). Texture descriptor based on partially self-Avoiding deterministic walker on networks, Expert Systems with Applications, 39(15), 11818-11829, ISSN 0957-4174. http://dx.doi.org/10.1016/j.eswa.2012.01.094.
24. Peteri, R., & Chetverikov, D. (2006). Qualitative characterization of dynamic textures for video retrieval. In Proceedings of the international conference on computer vision and graphics (Vol. 32, pp. 33-38).
25. R. Peteri, S. Fazekas, and M. Huiskes Dyntex: A comprehensive database of dynamic textures Pattern Recognition Letters 31 12 2010 1627 1632
26. Polana, R., & Nelson, R. C. (1997). Temporal texture and activity recognition. In Motion-based recognition.
27. Ravichandran, A., & Vidal, R. (2008). Video registration using dynamic textures. In ECCV (Vol. II, pp. 514-526).
28. Szummer, M., & Picard, R. W. (1996). Temporal texture modeling. In ICIP (Vol. III, pp. 823-826).
29. L. Vendramin, R.J.G.B. Campello, and E.R. Hruschka On the comparison of relative clustering validity criteria SDM 2009 SIAM 733 744
30. Vidal, R., & Singaraju, D. (2005). A closed form solution to direct motion segmentation. In CVPR (Vol. II, pp. 510-515).
31. Zhao, G. Y., & Pietikainen, M. (2006). Local binary pattern descriptors for dynamic texture recognition. In ICPR (pp. 211-214).
32. G. Zhao, and M. Pietikainen Dynamic texture recognition using local binary patterns with an application to facial expressions IEEE Transactions on Pattern Analysis and Machine Intelligence 29 6 2007 915 928
33. Zhong, H., Shi, J., & Visontai, M. (2004). Detecting unusual activity in video. In IEEE conference on computer vision and pattern recognition (pp. 819-826).