Image set based face recognition using self-regularized non-negative coding and adaptive distance metric learning

IEEE Transactions on Image Processing

Volumn 22, Issue 12, 2013, Pages 5252-5262

  Mian, Ajmal ^a   Hu, Yiqun ^b   Hartley, Richard ^c   Owens, Robyn ^a  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^b Paypal Innovation Team   (Singapore)

^c AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

distance metric learning; face recognition; Image set classification; nonnegative coding

Indexed keywords

ACCELERATED PROXIMAL GRADIENT METHODS; CONVEX OPTIMIZATION PROBLEMS; DISTANCE METRIC LEARNING; IMAGE SETS; NEAREST NEIGHBOR CLASSIFICATION; NON NEGATIVES; NON-NEGATIVITY CONSTRAINTS; STATE-OF-THE-ART METHODS;

CONVEX OPTIMIZATION; GRADIENT METHODS;

FACE RECOGNITION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; BIOMETRY; FACE; FACTUAL DATABASE; HISTOLOGY; HUMAN; IMAGE PROCESSING; METHODOLOGY; PRINCIPAL COMPONENT ANALYSIS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMETRIC IDENTIFICATION; DATABASES, FACTUAL; FACE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; PRINCIPAL COMPONENT ANALYSIS;

EID: 84886936934     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2013.2282996     Document Type: Article

References (56)

1. A. Bar-Hillel, T. Hertz, N. Shental, and D. Weinshall, "Learning a mahalanobis metric from equivalence constraints," J. Mach. Learn. Res., vol. 6, no. 6, pp. 937-965, 2005.
2. A. Beck and M. Teboulle, "A fast iterative shrinkage-thresholding algorithm for linear inverse problems," SIAM J. Imaging Sci. vol. 2, no. 1, pp. 183-202, Jan. 2009.
3. A. Fitzgibbon and A. Zisserman, "Joint manifold distance: A new approach to appearance based clustering," in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recognit., vol. 1. Jun. 2003, pp. 26-33.
4. A. Frome, Y. Singer, F. Sha, and J. Malik, "Learning globally-consistent local distance functions for shape-based image retrieval and classification," in Proc. IEEE ICCV, Oct. 2007, pp. 1-8.
5. D. Ross, J. Lim, R. Lin, and M. Yang, "Incremental learning for robust visual tracking," Int. J. Comput. Vis. vol. 77, nos. 1-3, pp. 125-141, 2008. (Pubitemid 351294740)
6. E. Oja, Subspace Methods of Pattern Recognition. New York, NY, USA: Wiley, 1983.
7. E. Xing, A. Ng, M. Jordan, and S. Russell, "Distance metric learning with application to clustering with side-information," in Proc. Annu. Conf. Neural Inf. Process. Syst., 2003, pp. 505-512.
8. G. Shakhnnarvovich, J. Fisher, and T. Darrell, "Face recognition from long-term observations," in Proc. ECCV, May 2002, pp. 851-865.
9. H. Cevikalp and B. Triggs, "Face recognition based on image sets," in Proc. IEEE CVPR, Jun. 2010, pp. 2567-2573.
10. H. Hotelling, "Relations between two sets of variates," Biometrika, vol. 28, nos. 3-4, pp. 321-377, Dec. 1936.
11. J. Beveridge, B. Draper, J. Chang, M. Kirby, H. Kley, and C. Peterson, "Principal angles separate subject illumination spaces in YDB and CMU-PIE," IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 2, pp. 351-363, Feb. 2009.
12. J. Davis, B. Kulis, P. Jain, S. Sra, and I. Dhillon, " Informationtheoretic metric learning," in Proc. 24th Int. Conf. Mach. Learn., 2007, pp. 209-216.
13. J. Globerson, S. Roweis, G. Hinton, and R. Salakhutdinov, "Neighbourhood components analysis," in Proc. Annu. Conf. NIPS, Nov. 2005, pp. 513-520.
14. J. Tenenbaum, V. de Silva, and J. Langford, "A global geometric framework for nonlinear dimensionality reduction," Science, vol. 290, no. 5500, pp. 2319-2323, Dec. 2000. (Pubitemid 32041577)
15. J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong, "Localityconstrained linear coding for image classification," in Proc. IEEE Int. CVPR, Jun. 2010, pp. 3360-3367.
16. K. Fukui and O. Yamaguchi, "The kernel orthogonal mutual subspace method and its application to 3D object recognition," in Proc. ACCV, Nov. 2007, pp. 467-476.
17. K. Fukui, B. Stenger, and O. Yamaguchi, "A framework for 3D object recognition using the kernel constrained mutual subspace method," in Proc. ACCV, Jan. 2006, pp. 315-324. (Pubitemid 43849423)
18. K. Lee, J. Ho, M. Yang, and D. Kriegman, "Video-vased face recognition using probabilistic appearance manifolds," in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recognit., Jun. 2003, pp. 313-320.
19. K. Weinberger and L. Saul, "Distance metric learning for large margin nearest neighbor classification," J. Mach. Learn. Res., vol. 10, no. 38, pp. 207-244, 2009.
20. K. Yu, T. Zhang, and Y. Gong, "Nonlinear learning using local coordinate coding," in Proc. Annu. Conf. Neural Inf. Process. Syst., vol. 22. 2009, pp. 801-808.
21. L. Wolf and A. Shashua, "Learning over sets using kernel principal angles," J. Mach. Learn. Res., vol. 4, no. 10, pp. 913-931, 2003.
22. L. Wolf, T. Hassner, and Y. Taigman, "Effective unconstrained face recognition by combining multiple descriptors and learned background statistics," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 10, pp. 1978-1990, Oct. 2011.
23. L. Yang and R. Jin, "Distance metric learning: A comprehensive survey," Ph.D. dissertation, Dept. Comput. Sci. Eng., Michigan State Univ., Lansing, MI, USA, May 2006.
24. L. Yang and R. Jin, "A overview of distance metric learning," in Proc. Comput. Vis. Pattern Recognit. Conf., Oct. 2007, pp. 1-8.
25. L. Yang, R. Jin, R. Sukthankar, and Y. Liu, "An efficient algorithm for local distance metric learning," in Proc. AAAI Conf. Artif. Intell., 2006, pp. 543-548. (Pubitemid 44705340)
26. M. Baghshah and S. Shouraki, "Semi-supervised metric learning using pairwise constraints," in Proc. Int. Joint Conf. Artif. Intell., 2009, pp. 1217-1222.
27. M. Kim, S. Kumar, V. Pavlovic, and H. Rowley, "Face tracking and recognition with visual constraints in real-world videos," in Proc. IEEE Int. Conf. CVPR, Jun. 2008, pp. 1-8.
28. M. Nishiyama, M. Yuasa, T. Shibata, T. Wakasugi, T. Kawahara, and O. Yamaguchi, "Recognizing faces of moving people by hierarchical image-set matching," in Proc. IEEE Int. CVPR, Jun. 2007, pp. 1-8.
29. M. Nishiyama, O. Yamaguchi, and K. Fukui, "Face recognition with the multiple constrained mutual subspace method," in Proc. Int. Conf. Audio Video-Based Biometric Person Authentication, 2005, pp. 71-80. (Pubitemid 41423023)
30. O. Arandjelovic and R. Cipolla, "A pose-wise linear illumination manifold model for face recognition using video," Comput. Vis. Image Understand., vol. 113, no. 1, pp. 113-125, Jan. 2009.
31. O. Arandjelovic, G. Shakhnarovich, J. Fisher, R. Cipolla, and T. Darrell, "Face recognition with image sets using manifold density divergence," in Proc. IEEE Int. Conf. CVPR, Jun. 2005, pp. 581-588.
32. O. Yamaguchi, K. Fukui, and K.-I. Maeda, "Face recognition using temporal image sequence," in Proc. 3rd IEEE Int. Conf. Autom. Face Gesture Recognit., Apr. 1998, pp. 318-323.
33. P. Belhumeur, J. Hespanha, and D. Kriegman, "Eigenfaces vs. fisherfaces: Recognition using class specific linear projection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 7, pp. 711-720, Jul. 1997. (Pubitemid 127762263)
34. P. Viola and M. J. Jones, "Robust real-time face detection," Int. J. Comput. Vis., vol. 57, no. 2, pp. 137-154, May 2004.
35. R. Gross and J. Shi, "The CMU motion of body, MoBo) database," Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA, Tech. Rep. CMU-RI-TR-01-18, Jun. 2001.
36. R. Wang and X. Chen, "Manifold discriminant analysis," in Proc. IEEE Int. Conf. CVPR, Jun. 2009, pp. 429-436.
37. R. Wang, S. Shan, X. Chen, and W. Gao, "Manifold-manifold distance with application to face recognition based on image set," in Proc. IEEE Int. Conf. CVPR, Jun. 2008, pp. 1-8.
38. S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge, U.K.: Cambridge Univ. Press, 2004.
39. S. Hoi, W. Liu, and S. Chang, "Semi-supervised distance metric learning for collaborative image retrieval and clustering," ACM Trans. Multimedia Comput., Commun., Appl., vol. 6, no. 3, pp. 1-26, 2010.
40. S. Roweis and L. Saul, "Nonlinear dimensionality reduction by locally linear embedding," Science, vol. 290, no. 5500, pp. 2323-2326, 2000. (Pubitemid 32041578)
41. T. Ahonen, A. Hadid, and M. Pietikainen, "Face description with local binary patterns: Application to face recognition," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 12, pp. 2037-2041, Dec. 2006. (Pubitemid 46405714)
42. T. Chin, K. Schindler, and D. Suter, "Incremental kernel SVD for face recognition with image sets," in Proc. IEEE 7th Int. Conf. Autom. FGR, Apr. 2006, pp. 461-466. (Pubitemid 44711392)
43. T. Kim and R. Cipolla, "On-line learning for maximizing orthogonality between subspaces and its application to image set-based face recognition," IEEE Trans. Image Process., vol. 19, no. 4, pp. 1067-1074, Apr. 2009.
44. T. Kim, J. Kittler, and R. Cipolla, "Incremental learning of locally orthogonal subspaces for set-based object recognition," in Proc. Brit. Mach. Vis. Conf., 2006, pp. 559-568.
45. T. Kim, O. Arandjelovic, and R. Cipolla, "Learning over sets using boosted manifold principle angles, (BoMPA)," in Proc. Brit. Mach. Vis. Conf., 2005, pp. 779-788.
46. T. Kim, O. Arandjelovic, and R. Cipolla, "Boosted manifold principal angles for image set-based recognition," Pattern Recognit., vol. 40, no. 9, pp. 2475-2484, 2007. (Pubitemid 46669592)
47. T. Kim, O. Arandjelovic, and R. Cipolla, "Discriminative learning and recognition of image set classes using canonical correlations," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 6, pp. 1005-1018, Jun. 2007. (Pubitemid 46667413)
48. T. Wang and P. Shi, "Kernel Grassmannian distances and discriminant analysis for face recognition from image sets," Pattern Recognit. Lett., vol. 30, no. 13, pp. 1161-1165, Oct. 2009.
49. W. Fan and D. Yeung, "Locally linear models on face appearance manifolds with application to dual-subspace based classification," in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recognit., Jun. 2006, pp. 1384-1390. (Pubitemid 44931482)
50. W. Liu, S. Ma, D. Tao, P. Liu, and J. Liu, "Semi-supervised sparse metric learning using althernative linearization optimization," in Proc. ACM Conf. Knowl. Discovery Data Mining, 2010, pp. 1139-1148.
51. W. Liu, X. Tian, D. Tao, and J. Liu, "Constrained metric learning via distance gap maximization," in Proc. AAAI Annu. Conf. Artif. Intell., 2010, pp. 518-524.
52. X. Li, K. Fukui, and N. Zheng, "Boosting constrained mutual subspace method for robust image-set based object recognition," in Proc. Int. Joint Conf. Artif. Intell., 2009, pp. 1132-1137.
53. X. Li, K. Fukui, and N. Zheng, "Image-set based face recognition using boosted global and local principal angles," in Proc. ACCV, Sep. 2009, pp. 323-332.
54. Y. Hu, A. Mian, and R. Owens, "Sparse approximated nearest points for image set classification," in Proc. IEEE Int. Conf. CVPR, Jun. 2011, pp. 121-128.
55. Y. Nesterov, "Gradient methods for minimizing composite objective function," Univ. Catholique de Louvain, Center Operations Res. Econometrics, Louvain-La-Neuve, Belgium, Tech. Rep. 2007076, Sep. 2007.
56. Z. Wang, Y. Hu, and L.-T. Chia, "Image-to-class distance metric learning for image classification," in Proc. Eur. Conf. Comput. Vis., 2010, pp. 706-719.