Subspace interpolation via dictionary learning for unsupervised domain adaptation

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

Volumn , Issue , 2013, Pages 692-699

  Ni, Jie ^a   Qiu, Qiang ^a   Chellappa, Rama ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DICTIONARY LEARNING; DIFFERENT DISTRIBUTIONS; DOMAIN ADAPTATION; FEATURE REPRESENTATION; MULTIPLE SOURCE; OPTIMAL DOMAIN; QUANTITATIVE MEASURES; STATE OF THE ART;

OBJECT RECOGNITION;

FACE RECOGNITION;

EID: 84887392643     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2013.95     Document Type: Conference Paper

References (33)

1. M. Aharon, M. Elad, and A. Bruckstein. K-SVD: An algorithm for designing of overcomplete dictionaries for sparse representation. IEEE Transactions on Signal Processing, 54(11):4311-4322, 2006. 2, 3, 5, 6
2. T. Ahonen, E. Rahtu, V. Ojansivu, and J. Heikkilä. Recognition of blurred faces using local phase quantization. In ICPR, pages 1-4, 2008. 5
3. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool. Speededup robust features (surf). Comput. Vis. Image Underst., 110(3):346-359, June 2008. 6
4. A. Bergamo and L. Torresani. Exploiting weakly-labeled web images to improve object classification: a domain adaptation approach. In NIPS, pages 181-189, 2010. 1
5. S. Biswas, G. Aggarwal, and R. Chellappa. Robust estimation of albedo for illumination-invariant matching and shape recovery. IEEE Trans. Pattern Anal. Mach. Intell., 31(5):884-899, May 2009. 5
6. S. Biswas, G. Aggarwal, and P. Flynn. Pose-robust recognition of low-resolution face images. In CVPR, pages 601-608, June 2011. 1
7. J. Blitzer, R. McDonald, and F. Pereira. Domain adaptation with structural correspondence learning. In Conference on Empirical Methods in Natural Language Processing, pages 120-128, 2006. 3
8. R. Chellappa, J. Ni, and V. M. Patel. Remote identification of faces: Problems, prospects, and progress. Pattern Recogn. Lett., 33(14):1849-1859, Oct. 2012. 1
9. H. Daumé III. Frustratingly easy domain adaptation. In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pages 256-263, June 2007. 3
10. L. Duan, D. Xu, I. W.-H. Tsang, and J. Luo. Visual event recognition in videos by learning from web data. IEEE Trans. Pattern Anal. Mach. Intell., 34(9):1667-1680, 2012. 3
11. M. Elad and M. Aharon. Image denoising via sparse and redundant representations over learned dictionaries. IEEE Transactions on Image Processing, 15(12):3736-3745, 2006. 2
12. K. Engan, S. Aase, and J. Hakon Husoy. Method of optimal directions for frame design. In ICASSP, pages 2443-2446, 1999. 4
13. B. Gong, Y. Shi, F. Sha, and K. Grauman. Geodesic flow kernel for unsupervised domain adaptation. In CVPR, pages 2066-2073, 2012. 1, 3, 5, 6
14. R. Gopalan, R. Li, and R. Chellappa. Domain adaptation for object recognition: An unsupervised approach. In ICCV, pages 999-1006, 2011. 1, 3, 5, 6
15. G. Griffin, A. Holub, and P. Perona. Caltech-256 object category dataset. Technical report, Caltech, 2007. 6
16. R. Gross, I. Matthews, and S. Baker. Appearance-based face recognition and light-fields. IEEE Trans. Pattern Anal. Mach. Intell., 26(4):449-465, April 2004. 5
17. I.-H. Jhuo, D. Liu, D. T. Lee, and S.-F. Chang. Robust visual domain adaptation with low-rank reconstruction. In CVPR, pages 2168-2175, 2012. 1, 3
18. B. Kulis, K. Saenko, and T. Darrell. What you saw is not what you get: Domain adaptation using asymmetric kernel transforms. In CVPR, pages 1785-1792, 2011. 3
19. A. Levin, Y. Weiss, F. Durand, and W. T. Freeman. Understanding and evaluating blind deconvolution algorithms. In CVPR, pages 1964-1971, 2009. 6
20. R. Li and T. Zickler. Discriminative virtual views for crossview action recognition. In CVPR, pages 2855-2862, 2012. 1
21. J. Liu, M. Shah, B. Kuipers, and S. Savarese. Cross-view action recognition via view knowledge transfer. In CVPR, pages 3209-3216, 2011. 1
22. J. Mairal, F. Bach, and J. Ponce. Task-driven dictionary learning. IEEE Trans. Pattern Anal. Mach. Intell., 34(4):791-804, 2012. 2
23. J. Mairal, F. Bach, J. Ponce, and G. Sapiro. Online dictionary learning for sparse coding. In ICML, pages 689-696, 2009. 2
24. J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman. Supervised dictionary learning. In NIPS, pages 1033-1040, 2008. 2
25. S. J. Pan, J. T. Kwok, and Q. Yang. Transfer learning via dimensionality reduction. In AAAI, pages 677-682, 2008. 3
26. S. J. Pan, I. W. Tsang, J. T. Kwok, and Q. Yang. Domain adaptation via transfer component analysis. In IJCAI, pages 1187-1192, 2009. 3
27. Q. Qiu, V. Patel, P. Turage, and R. Chellappa. Domain adaptive dictionary learning. In ECCV, pages 631-645, 2012. 3
28. K. Saenko, B. Kulis, M. Fritz, and T. Darrell. Adapting visual category models to new domains. In ECCV, pages 213-226, 2010. 1, 3, 6
29. Y. Shi and F. Sha. Information-theoretical learning of discriminative clusters for unsupervised domain adaptation. In ICML, 2012. 3
30. T. Sim, S. Baker, and M. Bsat. The cmu pose, illumination, and expression database. IEEE Trans. Pattern Anal. Mach. Intell., 25(12):1615-1618, 2003. 4, 5
31. C. Wang and S. Mahadevan. Manifold alignment without correspondence. In IJCAI, pages 1273-1278, 2009. 3
32. J. Wright, A. Y. Yang, A. Ganesh, S. S. Sastry, and Y. Ma. Robust face recognition via sparse representation. IEEE Trans. Pattern Anal. Mach. Intell., 31(2):210-227, Feb 2009. 2
33. J. Yang, R. Yan, and A. G. Hauptmann. Cross-domain video concept detection using adaptive svms. In ACM Multimedia, pages 188-197, 2007. 3