Describing textures in the wild

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2014, Pages 3606-3613

  Cimpoi, Mircea ^a   Maji, Subhransu ^b   Kokkinos, Iasonas ^c   Mohamed, Sammy ^d   Vedaldi, Andrea ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b TOYOTA TECHNOLOGICAL INSTITUTE   (Japan)

^c École Centrale Paris   (Germany)

^d NONE   (United States)

Author keywords

attribute; convolutional neural network; Fisher Vector; material; recognition; texture

Indexed keywords

CONVOLUTION; CONVOLUTIONAL NEURAL NETWORKS; LARGE DATASET; MATERIALS; OBJECT RECOGNITION; SEMANTICS; TEXTURES;

ATTRIBUTE; CONVOLUTIONAL NETWORKS; FISHER VECTORS; KEY CHARACTERISTICS; MATERIAL RECOGNITION; RECOGNITION; TEXTURE DESCRIPTORS; TEXTURE RECOGNITION;

IMAGE TEXTURE;

EID: 84911453074     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.461     Document Type: Conference Paper

References (42)

1. M. Amadasun and R. King. Textural features corresponding to textural properties. Systems, Man, and Cybernetics, 19(5), 1989.
2. R. Bajcsy. Computer description of textured surfaces. In IJCAI, IJCAI. Morgan Kaufmann Publishers Inc., 1973.
3. T. Berg, A. Berg, and J. Shih. Automatic attribute discovery and characterization from noisy web data. ECCV, 2010.
4. B. Berlin and P. Kay. Basic color terms: Their universality and evolution. Univ of California Press, 1991.
5. N. Bhushan, A. Rao, and G. Lohse. The texture lexicon: Understand-ing the categorization of visual texture terms and their relationship to texture images. Cognitive Science, 21(2):219-246, 1997.
6. L. Bourdev, S. Maji, and J. Malik. Describing people: A poselet-based approach to attribute classification. In ICCV, 2011.
7. B. Caputo, E. Hayman, and P. Mallikarjuna. Class-specific material categorisation. In ICCV, 2005.
8. G. Csurka, C. R. Dance, L. Dan, J. Willamowski, and C. Bray. Visual categorization with bags of keypoints. In Proc. ECCV Workshop on Stat. Learn. in Comp. Vision, 2004.
9. K. J. Dana, B. van Ginneken, S. K. Nayar, and J. J. Koenderink. Reflectance and texture of real world surfaces. ACM Transactions on Graphics, 18(1):1-34, 1999.
10. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei. ImageNet: A Large-Scale Hierarchical Image Database. In CVPR, 2009.
11. J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell. Decaf: A deep convolutional activation feature for generic visual recognition. In Proc. ICML, 2013.
12. A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth. Describing objects by their attributes. In CVPR, pages 1778-1785. IEEE, 2009.
13. V. Ferrari and A. Zisserman. Learning visual attributes. In NIPS, 2007.
14. J. M. Geusebroek, A. W. M. Smeulders, and J. van de Weijer. Fast anisotropic gauss filtering. IEEE Transactions on Image Processing, 12(8):938-943, 2003.
15. E. Hayman, B. Caputo, M. Fritz, and J.-O. Eklundh. On the significance of real-world conditions for material classification. ECCV, 2004.
16. H. Jégou, M. Douze, C. Schmid, and P. Pérez. Aggregating local descriptors into a compact image representation. In Proc. CVPR, 2010.
17. B. Julesz. Textons, the elements of texture perception, and their interactions. Nature, 290(5802):91-97, march 1981.
18. A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In Proc. NIPS, 2012.
19. N. Kumar, A. Berg, P. Belhumeur, and S. Nayar. Describable visual attributes for face verification and image search. PAMI, 33(10):1962-1977, 2011.
20. S. Lazebnik, C. Schmid, and J. Ponce. A sparse texture representation using local affine regions. PAMI, 28(8):2169-2178, 2005.
21. T. Leung and J. Malik. Representing and recognizing the visual appearance of materials using three-dimensional textons. International Journal of Computer Vision, 43(1):29-44, 2001.
22. D. G. Lowe. Object recognition from local scale-invariant features. In Proc. ICCV, 1999.
23. J. Malik and P. Perona. Preattentive texture discrimination with early vision mechanisms. JOSA A, 7(5), 1990.
24. T. Matthews, M. S. Nixon, and M. Niranjan. Enriching texture analysis with semantic data. In CVPR, June 2013.
25. T. Ojala, M. Pietikainen, and T. Maenpaa. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. PAMI, 24(7):971-987, 2002.
26. G. Oxholm, P. Bariya, and K. Nishino. The scale of geometric texture. In European Conference on Computer Vision, pages 58-71. Springer Berlin/Heidelberg, 2012.
27. G. Patterson and J. Hays. Sun attribute database: Discovering, annotating, and recognizing scene attributes. In CVPR, 2012.
28. F. Perronnin and C. R. Dance. Fisher kernels on visual vocabularies for image categorization. In CVPR, 2007.
29. F. Perronnin, J. Sánchez, and T. Mensink. Improving the Fisher kernel for large-scale image classification. In Proc. ECCV, 2010.
30. J. C. Platt. Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. In A. Smola, P. Bartlett, B. Schölkopf, and D. Schuurmans, editors, Advances in Large Margin Classifiers. Cambridge, 2000.
31. L. Sharan, C. Liu, R. Rosenholtz, and E. H. Adelson. Recognizing materials using perceptually inspired features. International Journal of Computer Vision, 103(3):348-371, 2013.
32. L. Sharan, R. Rosenholtz, and E. H. Adelson. Material perceprion: What can you see in a brief glance? Journal of Vision, 9:784(8), 2009.
33. G. Sharma, S. ul Hussain, and F. Jurie. Local higher-order statistics (lhs) for texture categorization and facial analysis. In Proc. ECCV. 2012.
34. L. Sifre and S. Mallat. Rotation, scaling and deformation invariant scattering for texture discrimination. In CVPR, June 2013.
35. H. Tamura, S. Mori, and T. Yamawaki. Textural features corresponding to visual perception. Systems, Man and Cybernetics, IEEE Transactions on, 8(6):460-473, june 1978.
36. R. Timofte and L. Van Gool. A training-free classification framework for textures, writers, and materials. In BMVC, Sept. 2012.
37. J. C. van Gemert, J.-M. Geusebroek, C. J. Veenman, and A. W. M. Smeulders. Kernel codebooks for scene categorization. In Proc. ECCV, 2008.
38. M. Varma and A. Zisserman. Texture classification: Are filter banks necessary? In CVPR, volume 2, pages II-691. IEEE, 2003.
39. M. Varma and A. Zisserman. A statistical approach to texture classification from single images. IJCV, 62(1):61-81, 2005.
40. A. Vedaldi and A. Zisserman. Efficient additive kernels via explicit feature maps. In CVPR, 2010.
41. J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong. Locality-constrained linear coding for image classification. Proc. CVPR, 2010.
42. Y. Xu, H. Ji, and C. Fermuller. Viewpoint invariant texture description using fractal analysis. IJCV, 83(1):85-100, jun 2009.