Model-driven domain adaptation on product manifolds for unconstrained face recognition

International Journal of Computer Vision

Volumn 109, Issue 1-2, 2014, Pages 110-125

  Ho, Huy Tho ^a   Gopalan, Raghuraman ^b  

^a UNIVERSITY OF MARYLAND   (United States)

^b AT AND T LABS RESEARCH   (United States)

Author keywords

Domain adaptation; Manifold learning; Tensor computation; Unconstrained face recognition

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); MATRIX ALGEBRA; TENSORS;

CLASSIFICATION ALGORITHM; COMPREHENSIVE EVALUATION; DOMAIN ADAPTATION; IMAGE FORMATION MODELS; KERNEL DISCRIMINANT ANALYSIS; MANIFOLD LEARNING; PROBABILISTIC APPROACHES; TENSOR REPRESENTATION;

FACE RECOGNITION;

EID: 84902242377     PISSN: 09205691     EISSN: 15731405     Source Type: Journal    
DOI: 10.1007/s11263-014-0720-x     Document Type: Article

References (70)

1. Arandjelović, O. (2009). Unfolding a face: From singular to manifold. In Proc. ACCV (pp. 203-213).
2. Arandjelović, O.; Shakhnarovich, G.; Fisher, J.; Cipolla, R.; Darrell, T. (2005). Face recognition with image sets using manifold density divergence. In Proc. CVPR (pp. 581-588).
3. Basri, R.; Jacobs, D. W. (2003). Lambertian reflectance and linear subspaces. The IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(2), 218-233.
4. Begelfor, E.; Werman, M. (2006). Affine invariance revisited. In Proc. CVPR (pp 2087-2094).
5. Ben-David, S.; Blitzer, J.; Crammer, K.; Kulesza, A.; Pereira, F.; Vaughan, J. W. (2010). A theory of learning from different domains. Machine Learning, 79(1), 151-175.
6. Biswas, S.; Aggarwal, G.; Chellappa, R. (2009). Robust estimation of albedo for illumination-invariant matching and shape recovery. The IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(5), 884-899.
7. Björck, A.; Golub, G. H. (1973). Numerical methods for computing angles between linear subspaces. Mathematics of Computations, 27, 579-594.
8. Blanz, V.; Vetter, T. (1999). A morphable model for the synthesis of 3D faces. In SIGGRAPH (pp. 187-194).
9. Brooks, M. J.; Horn, B. K. P. (1985). Shape and source from shading. In Proc. IJAI (pp. 932-936).
10. Cevikalp, H.; Triggs, B. (2010). Face recognition based on image sets. In Proc. CVPR (pp. 2567-2573).
11. Chen, Y.; Patel, V. M.; Phillips, P. J.; Chellappa, R. (2012). Dictionary-based face recognition from video. In Proc. ECCV (pp. 766-779).
12. Daumé, H, I. I. I.; Marcu, D. (2006). Domain adaptation for statistical classifiers. Journal of Artificial Intelligence Research, 26(1), 101-126.
13. Duan, L.; Tsang, I.; Xu, D.; Chua, T.-S. (2009). Domain adaptation from multiple sources via auxiliary classifiers. In Proc. ICML (pp. 289-296).
14. Duan, L.; Tsang, I.; Xu, D.; Chua, T.-S. (2012). Domain transfer multiple Kernel learning. The IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(3), 465-479.
15. Edelman, A.; Arias, T. A.; Smith, S. T. (1999). The geometry of algorithms with orthogonality constraints. The SIAM Journal on Matrix Analysis and Applications, 20, 303-353.
16. Gong, B.; Shi, Y.; Sha, F.; Grauman, K. (2012). Geodesic flow Kernel for unsupervised domain adaptation. In Proc. CVPR (pp. 2066-2073).
17. Gopalan, R.; Li, R.; Chellappa, R. (2011). Domain adaptation for object recognition: An unsupervised approach. In Proc. ICCV (pp. 999-1006).
18. Gopalan, R.; Taheri, S.; Turaga, P.; Chellappa, R. (2012). A blur-robust descriptor with applications to face recognition. The IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(6), 1220-1226.
19. Hamm, J.; Lee, D. (2008). Grassmann discriminant analysis: A unifying view on subspace-based learning. In Proc. ICML (pp. 376-383).
20. Hoffman, J.; Kulis, B.; Darrell, T.; Saenko, K. (2012). Discovering latent domains for multisource domain adaptation. In Proc. ECCV (pp. 702-715).
21. Hu, Y.; Mian, A. S.; Owens, R. (2011). Sparse approximated nearest points for image set classification. In Proc. CVPR (pp. 27-40).
22. Huang, G. B.; Jain, V.; Learned-Miller, E. (2007). Unsupervised joint alignment of complex images. In Proc. ICCV.
23. Huang, G. B.; Ramesh, M.; Berg, T.; Learned-Miller, E. (2007). Labeled faces in the wild: A database for studying face recognition in unconstrained environments. Technical Report 07-49, University of Massachusetts, Amherst.
24. Jhuo, I.-H.; Liu, D.; Lee, D.; Chang, S.-F. (2012). Robust visual domain adaptation with low-rank reconstruction. In Proc. CVPR (pp. 2168-2175).
25. Jia, H.; Martinez, A. M. (2008). Face recognition with occlusions in the training and testing sets. In Proc. FG (pp. 1-6).
26. Jia, H.; Martinez, A. M. (2009). Support vector machines in face recognition with occlusions. In Proc. CVPR (pp. 136-141).
27. Joliffe, I. T. (1986). Principal component analysis. Berlin: Springer.
28. Kim, T. K.; Kittler, J.; Cipolla, R. (2007). Discriminative learning and recognition of image set classes using canonical correlations. The IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(6), 1005-1018.
29. Kulis, B.; Saenko, K.; Darrell, T. (2011). What you saw is not what you get: Domain adaptation using asymmetric Kernel transforms. In Proc. CVPR (pp. 1785-1792).
30. Lee, J. M. (2010). Introduction to topological manifolds (2nd ed.). Berlin: Springer.
31. Lee, K. C.; Ho, J.; Kriegman, D. J. (2005). Acquiring linear subspaces for face recognition under variable lighting. The IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(5), 684-698.
32. Lee, K. C.; Ho, J.; Yang, M. H.; Kriegman, D. J. (2005). Visual tracking and recognition using probabilistic appearance manifolds. CVIU, 99(3), 303-331.
33. Li, H.; Hua, G.; Lin, Z.; Brandt, J.; Yang, J. (2013). Probabilistic elastic matching for pose invariant face recognition. In Proc. CVPR.
34. Li, Y.; Du, Y.; Lin, X. (2005). Kernel-based multifactor analysis for image synthesis and recognition. In Proc. ICCV (pp. 114-119).
35. Liu, J.; Chen, S.; Zhou, Z.; Tan, X. (2007). Single image subspace for face recognition. In Proc. AMFG (pp. 205-219).
36. Lowe, D. J. (2004). Distinctive image features from scale-invariant keypoints. IJCV, 60(2), 91-110.
37. Lu, J.; Tan, Y.P.; Wang, G. (2011). Discriminative multi-manifold analysis for face recognition from a single training sample per person. In Proc. ICCV (pp. 1943-1950).
38. Lui, Y. M. (2012). Advances in matrix manifolds for computer vision. Image and Vision Computing, 30, 380-388.
39. Lui, Y. M.; Beveridge, J. R. (2008). Grassmann registration manifolds for face recognition. In Proc. ECCV (vol. 2, pp. 44-57).
40. Lui, Y. M.; Beveridge, J. R.; Kirby, M. (2010). Action classifications on product manifolds. In Proc. CVPR (pp. 833-839).
41. Martinez, A. M. (2009). Recognizing imprecisely localized, partially occluded, and expression variant faces from a single sample per class. The IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(6), 748-763.
42. Martinez, A. M.; Benavente, R. (1998). The AR Face Database. CVC Technical Report, 24.
43. Ni, J.; Qiu, Q.; Chellappa, R. (2013). Subspace interpolation via dictionary learning for unsupervised domain adaptation. In Proc. CVPR.
44. Nishiyama, M.; Hadid, A.; Takeshima, H.; Shotton, J.; Kozakaya, T.; Yamaguchi, O. (2011). Facial deblur inference using subspace analysis for recognition of blurred faces. The IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(4), 838-845.
45. Nowak, E.; Jurie, F. (2007). Learning visual similarities measures for comparing never seen objects. In Proc. CVPR.
46. Ojala, T.; Pietikäinen, M.; Mäenpää, T. (2002). Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. The IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7), 971-987.
47. Ojansivu, V.; Heikkilä, J. (2008). Blur insensitive texture classification using local phase quantization. In Proc. ICISP (pp. 236-243).
48. Park, S. W.; Savvides, M. (2010). An extension of multifactor analysis for face recognition based on submanifold learning. In Proc. CVPR (pp. 2645-2652).
49. Park, S. W.; Savvides, M. (2011a). Multifactor analysis based on factor-dependent geometry. In Proc. CVPR (pp. 2817-2824).
50. Park, S. W.; Savvides, M. (2011b). The multifactor extension of grassmann manifolds for face recognition. In Proc. FG (pp. 464-469).
51. Pinto, N.; Dicarlo, J. J.; Cox, D. D. (2009). How far can you get with a modern face recognition test set using only simple features. In Proc. CVPR.
52. Qiu, Q.; Patel, V.; Turaga, P.; Chellappa, R. (2012). Domain adaptive dictionary learning. In Proc. ECCV (pp. 631-645).
53. Roweis, S. T.; Saul, L. K. (2000). Nonlinear dimensionality reduction by locally linear embedding. Science, 290, 2323-2326.
54. Saenko, K.; Kulis, B.; Fritz, M.; Darrell, T. (2010). Adapting visual category models to new domains. In Proc. ECCV (pp. 213-226).
55. Sanderson, C.; Lovell, B. C. (2009). Multi-region probabilistic histograms for robust and scalable identity inference. In Proc. ICB (pp. 199-208).
56. Shakhnarovich, G.; Fisher, J. W.; Darell, T. (2002). Face recognition from long term observations. In Proc. ECCV (pp. 851-868).
57. Shekhar, S.; Patel, V.; Nguyen, H.; Chellappa, R. (2013). Generalized domain-adaptive dictionaries. In Proc. CVPR.
58. Shi, Y.; Sha, F. (2012). Information-theoretical learning of discriminative clusters for unsupervised domain adaptation. In Proc. ICML.
59. Sim, T.; Baker, S.; Bsat, M. (2003). The CMU pose, illumination, and expression database. The IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(12), 1615-1618.
60. Tenenbaum, J. B.; de Silva, V.; Langford, J. C. (2000). A global geometric framework for non-linear dimensionality reduction. Science, 290, 2319-2323.
61. Vageeswaran, P.; Mitra, K.; Chellappa, R. (2013). Blur and illumination robust face recognition via set-theoretic characterization. IEEE Transactions on Image Processing, 22(4), 1362-1372.
62. Vapnik, V. N. (1998). Statistical Learning Theory. New York: Wiley.
63. Vasilescu, M. A. O.; Terzopoulos, D. (2002). Multilinear analysis of image ensembles. In Proc. ECCV (pp. 447-460).
64. Vasilescu, M. A. O.; Terzopoulos, D. (2007). Multilinear projection for appearance-based recognition in the tensor framework. In Proc. ICCV (pp. 1-8).
65. Viola, P.; Jones, M. (2001). Rapid object detection using a boosted cascade of simple features. In Proc. CVPR (pp. 511-518).
66. Wang, R.; Chen, X. (2009). Manifold discriminant analysis. In Proc. CVPR (pp. 429-436).
67. Wolf, L.; Hassner, T.; Taigman, Y. (2008). Descriptor based methods in the wild. In Faces in real-life images workshop in ECCV.
68. Yang, J.; Yan, R.; Hauptmann, A. (2007). Cross-domain video concept detection using adaptive SVMs. In Proc. ACM MM (pp. 188-197).
69. Zhao, W.; Chellappa, R.; Phillips, P. J.; Rosenfeld, A. (2003). Face recognition: A literature survey. ACM Computing Surveys, 35(4), 399-458.
70. Zheng, J.; Liu, M.-Y.; Chellappa, R.; Phillips, J. (2012). A grassmann manifold-based domain adaptation approach. In Proc. ICPR (pp. 2095-2099).