Learning predictable binary codes for face indexing

Pattern Recognition

Volumn 48, Issue 10, 2015, Pages 3160-3168

  He, Ran ^a   Cai, Yinghao ^a   Tan, Tieniu ^a   Davis, Larry ^b  

^a INSTITUTE OF AUTOMATION   (China)

^b Institute of Advanced Computer Science   (United States)

Author keywords

Binary codes; Face index; Feature learning; Hashing; Large scale

Indexed keywords

BINARY CODES; COMBINATORIAL OPTIMIZATION; HASH FUNCTIONS; INDEXING (OF INFORMATION); ITERATIVE METHODS; MAXIMUM PRINCIPLE; QUERY PROCESSING;

COMBINATORIAL OPTIMIZATION PROBLEMS; EXPECTATION-MAXIMIZATION METHOD; FACE INDEX; FEATURE LEARNING; FEATURE REPRESENTATION; HASHING; LARGE SCALE; STORAGE REQUIREMENTS;

FACE RECOGNITION;

EID: 84931562214     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2015.03.016     Document Type: Article

References (60)

1. D. Chen, X. Cao, F. Wen, J. Sun, Blessing of dimensionality: high-dimensional feature and its efficient compression for face verification, in: CVPR, 2013.
2. Z. Wu, Q. Ke, J. Sun, and H.-Y. Shum Scalable face image retrieval with identity-based quantization and multireference reranking IEEE TPAMI 33 10 2011 1991 2001
3. Z. Stone, T. Zickler, and T. Darrell Toward large-scale face recognition using social network context Proc. IEEE 98 8 2010 1408 1415
4. R. He, W.-S. Zheng, B.-G. Hu, and X.-W. Kong Two-stage nonnegative sparse representation for large-scale face recognition IEEE TNNLS 24 1 2013 35 46
5. D. Yi, Z. Lei, Y. Hu, S. Z. Li, Fast Matching by 2 Lines of Code for Large Scale Face Recognition Systems, Technical Report, CASIA, arXiv:1302.7180, 2013.
6. B. Kulis, T. Darrell, Learning to hash with binary reconstructive embeddings, in: NIPS, 2009, pp. 1042-1050.
7. B. Kulis, K. Grauman, Kernelized locality-sensitive hashing for scalable image search, in: ICCV, 2009.
8. M. Raginsky, S. Lazebnik, Locality-sensitive binary codes from shift-invariant kernels, in: NIPS, 2009.
9. Y. Weiss, A. Torralba, R. Fergus, Spectral hashing, in: NIPS, 2009, pp. 1753-1760.
10. M.M. Bronstein, A.M. Bronstein, F. Michel, N. Paragios, Data fusion through cross-modality metric learning using similarity-sensitive hashing, in: CVPR, 2010.
11. K. He, F. Wen, J. Sun, K-means hashing: an affinity-preserving quantization method for learning binary compact codes, in: CVPR, 2013.
12. Y. Mu, G. Hua, W. Fan, S.-F. Chang, Hash-svm: Scalable kernel machines for large-scale visual classification, in: CVPR, 2014.
13. G. Lin, C. Shen, J. Wu, Optimizing ranking measures for compact binary code learning, in: ECCV, 2014.
14. G. Lin, C. Shen, Q. Shi, A. van den Hengel, D. Suter, Fast supervised hashing with decision trees for high-dimensional data, in: CVPR, 2014.
15. G. Hinton, and R. Salakhutdinov Discovering binary codes for documents by learning deep generative models Cognit. Sci. 411 2010 1 18
16. K. Grauman, and R. Fergus Learning binary hash codes for large-scale image search Mach. Learn. Comput. Vis. 411 2013 49 87
17. H. Jegou, M. Douze, and C. Schmid Product quantization for nearest neighbor search IEEE TPAMI 33 1 2011 117 128
18. J. Wang, S. Kumar, S.F. Chang, Sequential projection learning for hashing with compact codes, in: ICML, 2010, pp. 1753-1760.
19. J. Wang, S. Kumar, S.F. Chang, Semi-supervised hashing for scalable image retrieval, in: CVPR, 2010.
20. S. Biswas, G. Aggarwal, and R. Chellappa An efficient and robust algorithm for shape indexing and retrieval IEEE Trans. Multimed. 12 5 2010 372 385
21. W. Liu, J. Wang, S. Kumar, S.-F. Chang, Hashing with graphs, in: ICML, 2011.
22. W. Kong, W.-J. Li, M. Guo, Manhattan hashing for large-scale image retrieval, in: SIGIR, 2012.
23. Y. Gong, S. Lazebnik, Iterative quantization: a procrustean approach to learning binary codes, in: CVPR, 2011.
24. W. Liu, J. Wang, R. Ji, Y. Jiang, S. Chang, Supervised hashing with kernels, in: CVPR, 2012, pp. 2074-2081.
25. C. Strecha, A.M. Bronstein, M.M. Bronstein, and P. Fua LDAHash: improved matching with smaller descriptors IEEE TPAMI 34 1 2012 1 14
26. Y. Kang, S. Kim, S. Choi, Deep learning to hash with multiple representations, in: ICDM, 2012, pp. 930-935.
27. M. Rastegari, J. Choi, S. Fakhraei, H. Daume, L.S. Davis, Predictable dual-view hashing, in: ICML, 2013.
28. Y. Zhen, D. Yeung, Co-regularized hashing for multimodal data, in: CVPR, 2012.
29. G. Ding, Y. Guo, J. Zhou, Collective matrix factorization hashing for multimodal data, in: CVPR, 2014.
30. D.C.L. Ngo, A.B.J. Teoh, A. Goh, Eigenspace-based face hashing, in: Biometric Authentication, 2004, pp. 195-199.
31. A.T.B. Jin, D.N.C. Ling, and A. Goh Biohashing two factor authentication featuring fingerprint data and tokenised random number Pattern Recognit. 37 2004 2245 2255
32. A. Kong, K.-H. Cheung, D. Zhang, M. Kamel, and J. You An analysis of biohashing and its variants Pattern Recognit. 39 7 2006 1359 1368
33. Z. Zeng, T. Fang, S. Shah, I.A. Kakadiaris, Local feature hashing for face recognition, in: BTAS, 2009, pp. 119-126.
34. Q. Shi, H. Li, C. Shen, Rapid face recognition using hashing, in: CVPR, 2010, pp. 2753-2760.
35. J. Yan, Z. Lei, D. Yi, S. Z.Li, Towards incremental and large scale face recognition, in: IJCB, 2011, pp. 1-6.
36. D. Sattar, S. Mohsin, K. Ayub, M. Raza, S. Mohsin, Enhanced and fast face recognition by hashing algorithm, J. Appl. Res. Technol. 10(4) (2012) 607-617.
37. B.-C. Chen, Y.-Y. Chen, Y.-H. Kuo, W. H. Hsu, Scalable face image retrieval using attribute-enhanced sparse codewords, IEEE Trans. Multimed. 15(5) (2013) 1163-1173.
38. R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin Liblinear a library for large linear classification JMLR 9 2008 1871 1874
39. Z. Lei, R. Chu, R. He, S. Liao, S. Z. Li, Face recognition by discriminant analysis with Gabor tensor representation, in: IAPR/IEEE International Conference on Biometrics, 2007.
40. Y. Bengio, A. Courville, and P. Vincent Representation learning a review and new perspectives TPAMI 35 8 2013 1798 1828
41. Y.L. Cun, B. Boser, J.S. Denker, D. Henderson, R.E. Howard, W. Hubbard, L. D. Jackel, Hand-written digit recognition with a back-propagation network, in: NIPS, 1990.
42. Y. Taigman, M. Yang, M. A. Ranzato, L. Wolf, Deepface: Closing the gap to human-level performance in face verification, in: CVPR, 2014.
43. Y. Sun, X. Wang, X. Tang, Deep learning face representation from predicting 1000 classes, in: CVPR, 2014.
44. A.M. Martinez, R. Benavente, The AR Face Database, Computer Vision Center (CVC), Technical Report.
45. P.J. Phillips, P.J. Flynn, T. Scruggs, K. Bowyer, J. Chang, K. Hoffman, J. Marques, J. Min, W. Worek, Overview of the face recognition grand challenge, in: CVPR, 2005.
46. M. Kim, S. Kumar, V. Pavlovic, Rowley, Face tracking and recognition with visual constraints in real-world videos, in: CVPR, 2008.
47. A. Gionis, P. Indyk, R. Motwani, Similarity search in high dimensions via hashing, in: VLDB, 1999.
48. J. Wright, A.Y. Yang, A. Ganesh, S.S. Sastry, and Y. Ma Robust face recognition via sparse representation IEEE TPAMI 31 2 2009 210 227
49. R. He, W.-S. Zheng, and B.-G. Hu Maximum correntropy criterion for robust face recognition IEEE TPAMI 33 8 2011 1561 1576
50. K. Wang, R. He, W. Wang, L. Wang, T. Tan, Learning coupled feature spaces for cross-modal matching, in: ICCV, 2013.
51. T. Kim, O. Arandjelovic, and R. Cipolla Discriminative learning and recognition of image set classes using canonical correlations IEEE TPAMI 29 2007 1005 1018
52. R. Wang, S.G. Shan, X.L. Chen, W. Gao, Manifold-manifold distance with application to face recognition based on image set, in: CVPR, 2008.
53. Y. Hu, A. Mian, R. Owens, Sparse approximated nearest points for image classification, in: ICCV, 2011.
54. Y.C. Chen, V. Patel, S. Shekhar, R. Chellappa, P. Phillips, Sparse approximated nearest points for image classification, in: IEEE Conference on Automatic Face and Gesture Recognition, 2013.
55. R. Wang, H. Guo, L. Davis, Q. Dai, Covariance discriminative learning: a natural and efficient approach to image set classification, in: CVPR, 2012.
56. G. Zhang, R. He, L. Davis, Jointly learning dictionary and subspace structure for video-based face recognition, in: ACCV, 2014.
57. Z. Cui, H. Zhang, S. Lao, X. Chen, Image sets alignment for video-based face recognition, in: CVPR, 2012.
58. M. Yang, P. Zhu, L. V. Gool, L. Zhang, Face recognition based on regularized nearest points between image sets, in: IEEE Conference on Automatic Face and Gesture Recognition, 2013.
59. E.G. Ortiz, A. Wright, M. Shah, Face recognition in movie trailers via mean sequence sparse representation-based classification, in: CVPR, 2013.
60. G.B. Huang, M. Ramesh, T. Berg, E. Learned-Miller, Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments, Technical Report, University of Massachusetts, 2007.