Learning a discriminative dictionary for sparse coding via label consistent K-SVD

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

Volumn , Issue , 2011, Pages 1697-1704

  Jiang, Zhuolin ^a   Lin, Zhe ^b   Davis, Larry S ^a  

^a UNIVERSITY OF MARYLAND   (United States)

^b ADOBE RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ERRORS; LEARNING ALGORITHMS; OBJECT RECOGNITION;

CLASSIFICATION ERRORS; CONSISTENT CONSTRAINT; DICTIONARY LEARNING; DISCRIMINATIVE DICTIONARIES; OBJECT CATEGORY RECOGNITION; OBJECTIVE FUNCTIONS; OVER-COMPLETE DICTIONARIES; RECONSTRUCTION ERROR;

CODES (SYMBOLS);

EID: 80052901219     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2011.5995354     Document Type: Conference Paper

References (34)

1. M. Aharon, M. Elad, and A. Bruckstein. K-svd: An algorithm for designing overcomplete dictionries for sparse representation. IEEE Trans. on Signal Processing, 54(1):4311-4322, 2006.
2. O. Boiman, E. Shechtman, and M. Irani. In defense of nearest-neighor based image classification, 2008. CVPR.
3. Y. Boureau, F. Bach, Y. LeCun, and J. Ponce. Learning mid-level features for recognition, 2010. CVPR.
4. D. Bradley and J. Bagnell. Differential sparse coding, 2008. NIPS.
5. M. Elad and M. Aharon. Image denosing via sparse and redundant representations over learned dictionaries. IEEE Trans. Img. Proc., 54(12):3736-3745, 2006.
6. K. Engan, S. Aase, and J. Husy. Frame based signal compression using method of optimal directions (mod), 1999. IEEE Intern. Symp. Circ. Syst., 1999.
7. L. FeiFei, R. Fergus, and P. Perona. Learning generative visual models from few training samples: An incremental bayesian appoach tested on 101 object categories, 2004. CVPR Workshop on Generative Model Based Vision.
8. J. Gemert, J. Geusebroek, C. Veenman, and A. Smeulders. Kernel codebooks for scene categorization, 2008. ECCV.
9. A. Georghiades, P. Belhumeur, and D. Kriegman. From few to many: Illumination cone models for face recognition under variable lighting and pose. TPAMI, 23(6):643-660, 2001.
10. G. Golub, P. Hansen, and D. O'leary. Tikhonov regularization and total least squares. SIM J. Matrix Anal. Appl., 21(1):185-194, 1999.
11. G. Griffin, A. Holub, and P. Perona. Caltech-256 object category dataset, 2007. CIT Technical Report 7694.
12. R. Grosse, R. Raina, H. Kwong, and A. Y. Ng. Shift-invariant sparse coding for audio classification, 2007. Conf. on Uncertainty in AI.
13. K. Huang and S. Aviyente. Sparse representation for signal classification, 2007. NIPS.
14. P. Jain, B. Kullis, and K. Grauman. Fast image search for learned metrics, 2008. CVPR.
15. S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories, 2007. CVPR.
16. H. Lee, A. Battle, R. Raina, and A. Y. Ng. Efficient sparse coding algorithms, 2006. NIPS.
17. X. Lian, Z. Li, B. Lu, and L. Zhang. Max-margin dictionary learning for multiclass image categorization, 2010. ECCV.
18. J. Mairal, F. Bach, J. Ponce, and G. Sapiro. Online learning for matrix factorization and sparse coding. Journal of Machine Learning Research 11, pages 19-60, 2010.
19. J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman. Discriminative learned dictionaries for local image analysis, 2008. CVPR.
20. J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman. Supervised dictionary learning, 2009. NIPS.
21. J. Mairal, M. Leordeanu, F. Bach, M. Hebert, and J. Ponce. Discriminative sparse image models for class-specific edage detection and image interpretation, 2008. ECCV.
22. J. Marial, M. Elad, and G. Sapiro. Sparse representation for color image restoration. IEEE Trans. Img. Proc., 2008.
23. A. Martinez and R. Benavente. The ar face database, 1998. CVC Technical Report 24.
24. D. Pham and S. Venkatesh. Joint learning and dictionary construction for pattern recognition, 2008. CVPR.
25. M. Ranzato, C. Poultney, S. Chopra, and Y. LeCun. Efficient learning of sparse representations with an energy-based model, 2006. NIPS.
26. F. Rodriguez and G. Sapiro. Sparse representations for image classification: Learning discriminative and reconstructive non-parametric dictionaryies, 2007. IMA Preprint 2213.
27. J. Wang, J. Yang, K. Yu, F. Lv, T. huang, and Y. Gong. Locality-constrained linear coding for image classification, 2010. CVPR.
28. J. Wright, M. Yang, A. Ganesh, S. Sastry, and Y. Ma. Robust face recognition via sparse representation. TPAMI, 31(2):210-227, 2009.
29. J. Yang, K. Yu, Y. Gong, and T. Huang. Linear spatial pyramid matching using sparse coding for image classification, 2009. CVPR.
30. J. Yang, K. Yu, and T. Huang. Supervised translation-invariant sparse coding, 2010. CVPR.
31. L. Yang, R. Jin, R. Sukthankar, and F. Jurie. Unifying discriminative visual codebook genearation with classifier training for object category recognition, 2008. CVPR.
32. H. Zhang, A. Berg, M. Maire, and J. Malik. Svm-knn: Discriminative nearest neighbor classification for visual category recognition, 2006. CVPR.
33. Q. Zhang and B. Li. Discriminative k-svd for dictionary learning in face recognition, 2010. CVPR.
34. W. Zhang, A. Surve, X. Fern, and T. Dietterich. Learning non-redundant codebooks for classifying complex objects, 2009. ICML.