Structure Sensitive Hashing with Adaptive Product Quantization

IEEE Transactions on Cybernetics

Volumn 46, Issue 10, 2016, Pages 2252-2264

  Liu, Xianglong ^a   Du, Bowen ^a   Deng, Cheng ^b   Liu, Ming ^a   Lang, Bo ^a  

^a BEIHANG UNIVERSITY   (China)

^b XIDIAN UNIVERSITY   (China)

Author keywords

Adaptive product quantization; locality sensitive hashing (LSH); nearest neighbor search; structure sensitive; unsupervised hashing

Indexed keywords

ALGORITHMS; CODES (SYMBOLS); COMPUTATIONAL EFFICIENCY; HAMMING DISTANCE; NEAREST NEIGHBOR SEARCH; OPTIMIZATION; SEMANTICS;

ALTERNATING OPTIMIZATIONS; ATTRACTIVE SOLUTIONS; GLOBAL AND LOCAL STRUCTURES; HASHING ALGORITHMS; PRODUCT QUANTIZATIONS; SPECTRAL EMBEDDING; STRUCTURE-SENSITIVE; THEORETICAL GUARANTEES;

HASH FUNCTIONS;

EID: 84943156754     PISSN: 21682267     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCYB.2015.2474742     Document Type: Article

References (61)

1. G. Shakhnarovich, P. Viola, and T. Darrell, "Fast pose estimation with parameter-sensitive hashing, " in Proc. CVPR, Madison, WI, USA, 2003, pp. 750-757.
2. J. Wang, S. Kumar, and S.-F. Chang, "Sequential projection learning for hashing with compact codes, " in Proc. ICML, Haifa, Israel, 2010, pp. 1127-1134.
3. W. Liu, J. Wang, R. Ji, Y.-G. Jiang, and S.-F. Chang, "Supervised hashing with kernels, " in Proc. CVPR, Providence, RI, USA, 2012, pp. 2074-2081.
4. J. He et al., "Mobile product search with bag of hash bits and boundary reranking, " in Proc. CVPR, Providence, RI, USA, 2012, pp. 3005-3012.
5. L. Chen, D. Xu, I. W.-H. Tsang, and X. Li, "Spectral embedded hashing for scalable image retrieval, " IEEE Trans. Cybern., vol. 44, no. 7, pp. 1180-1190, Jul. 2013.
6. Z. Jin et al., "Fast and accurate hashing via iterative nearest neighbors expansion, " IEEE Trans. Cybern., vol. 44, no. 11, pp. 2167-2177, Nov. 2014.
7. J. Song, Y. Yang, X. Li, Z. Huang, and Y. Yang, "Robust hashing with local models for approximate similarity search, " IEEE Trans. Cybern., vol. 44, no. 7, pp. 1225-1236, Jul. 2014.
8. H. Yang et al., "Adaptive object retrieval with kernel reconstructive hashing, " in Proc. CVPR, Columbus, OH, USA, 2014, pp. 1955-1962.
9. Z. Jin, C. Li, Y. Lin, and D. Cai, "Density sensitive hashing, " IEEE Trans. Cybern., vol. 44, no. 8, pp. 1362-1371, Aug. 2014.
10. X. Liu, J. He, and B. Lang, "Multiple feature kernel hashing for large-scale visual search, " Pattern Recognit., vol. 47, no. 2, pp. 748-757, Feb. 2014.
11. T. Dean et al., "Fast, accurate detection of 100, 000 object classes on a single machine, " in Proc. CVPR, Portland, OR, USA, 2013, pp. 1-8.
12. P. Jain, S. Vijayanarasimhan, and K. Grauman, "Hashing hyperplane queries to near points with applications to large-scale active learning, " in Proc. NIPS, Vancouver, BC, Canada, 2010, pp. 928-936.
13. W. Liu, J. Wang, Y. Mu, S. Kumar, and S.-F. Chang, "Compact hyperplane hashing with bilinear functions, " in Proc. ICML, Edinburgh, U. K., 2012, pp. 17-24.
14. Y. Mu, G. Hua, W. Fan, and S.-F. Chang, "Hash-SVM: Scalable kernel machines for large-scale visual classification, " in Proc. CVPR, Columbus, OH, USA, 2014, pp. 979-986.
15. C. Deng, X. Liu, Y. Mu, and J. Li, "Large-scale multi-task image labeling with adaptive relevance discovery and feature hashing, " Signal Process., vol. 112, pp. 137-145, Jul. 2015.
16. X. Liu, J. He, C. Deng, and B. Lang, "Collaborative hashing, " in Proc. CVPR, Columbus, OH, USA, 2014, pp. 2147-2154.
17. J. Cheng, C. Leng, J. Wu, H. Cui, and H. Lu, "Fast and accurate image matching with cascade hashing for 3D reconstruction, " in Proc. CVPR, Columbus, OH, USA, 2014, pp. 1-8.
18. P. Indyk and R. Motwani, "Approximate nearest neighbors: Towards removing the curse of dimensionality, " in Proc. ACM STOC, Dallas, TX, USA, 1998, pp. 604-613.
19. M. S. Charikar, "Similarity estimation techniques from rounding algorithms, " in Proc. ACM STOC, Montreal, QC, Canada, 2002, pp. 380-388.
20. Y. Gong and S. Lazebnik, "Iterative quantization: A procrustean approach to learning binary codes, " in Proc. CVPR, Providence, RI, USA, 2011, pp. 817-824.
21. M. Norouzi and D. J. Fleet, "Cartesian k-means, " in Proc. CVPR, Portland, OR, USA, 2013, pp. 3017-3024.
22. Z. Jin et al., "Complementary projection hashing, " in Proc. ICCV, Sydney, NSW, Australia, 2013, pp. 257-264.
23. Y. Lin, R. Jin, D. Cai, S. Yan, and X. Li, "Compressed hashing, " in Proc. CVPR, Portland, OR, USA, 2013, pp. 446-451.
24. X. Liu, Y. Mu, D. Zhang, B. Lang, and X. Li, "Large-scale unsupervised hashing with shared structure learning, " IEEE Trans. Cybern., vol. 45, no. 9, pp. 1811-1822, Sep. 2014.
25. B. Kulis and K. Grauman, "Kernelized locality-sensitive hashing for scalable image search, " in Proc. ICCV, Kyoto, Japan, 2009, pp. 2130-2137.
26. J. He, W. Liu, and S.-F. Chang, "Scalable similarity search with optimized kernel hashing, " in Proc. ACM SIGKDD, Washington, DC, USA, 2010, pp. 1129-1138.
27. J.-P. Heo, Y. Lee, J. He, S.-F. Chang, and S.-E. Yoon, "Spherical hashing, " in Proc. CVPR, Providence, RI, USA, 2012, pp. 2957-2964.
28. K. He, F. Wen, and J. Sun, "K-means hashing: An affinity-preserving quantization method for learning binary compact codes, " in Proc. CVPR, Portland, OR, USA, 2013, pp. 2938-2945.
29. Y. Weiss, A. Torralba, and R. Fergus, "Spectral hashing, " in Proc. NIPS, Vancouver, BC, Canada, 2008, pp. 1753-1760.
30. W. Liu, J. Wang, S. Kumar, and S.-F. Chang, "Hashing with graphs, " in Proc. ICML, Bellevue, WA, USA, 2011, pp. 1-8.
31. W. Liu, C. Mu, S. Kumar, and S.-F. Chang, "Discrete graph hashing, " in Proc. NIPS, Montreal, QC, Canada, 2014, pp. 3419-3427.
32. Y. Mu, J. Shen, and S. Yan, "Weakly-supervised hashing in kernel space, " in Proc. CVPR, San Francisco, CA, USA, 2010, pp. 3344-3351.
33. J. Wang, S. Kumar, and S.-F. Chang, "Semi-supervised hashing for scalable image retrieval, " in Proc. CVPR, San Francisco, CA, USA, 2010, pp. 3424-3431.
34. X. Liu, Y. Mu, B. Lang, and S.-F. Chang, "Mixed image-keyword query adaptive hashing over multilabel images, " ACM Trans. Multimedia Comput. Commun. Appl., vol. 10, no. 2, Feb. 2014, Art. ID 22.
35. J. Song, Y. Yang, Z. Huang, H. T. Shen, and R. Hong, "Multiple feature hashing for real-time large scale near-duplicate video retrieval, " in Proc. ACM MM, Scottsdale, AZ, USA, 2011, pp. 423-432.
36. Q. Lv, W. Josephson, Z. Wang, M. Charikar, and K. Li, "Multi-probe LSH: Efficient indexing for high-dimensional similarity search, " in Proc. VLDB, Vienna, Austria, 2007, pp. 950-961.
37. H. Xu et al., "Complementary hashing for approximate nearest neighbor search, " in Proc. ICCV, Barcelona, Spain, 2011, pp. 1631-1638.
38. W. Kong and W.-J. Li, "Double-bit quantization for hashing, " in Proc. AAAI, Toronto, ON, Canada, 2012, pp. 2604-2623.
39. X. Liu, J. He, B. Lang, and S.-F. Chang, "Hash bit selection: A unified solution for selection problems in hashing, " in Proc. CVPR, Portland, OR, USA, 2013, pp. 1570-1577.
40. C. Deng, H. Deng, X. Liu, and Y. Yuan, "Adaptive multi-bit quantization for hashing, " Neurocomputing, vol. 151, pp. 319-326, Mar. 2015.
41. Q. Wang, B. Shen, S. Wang, L. Li, and L. Si, "Binary codes embedding for fast image tagging with incomplete labels, " in Proc. ECCV, Zurich, Switzerland, 2014, pp. 425-439.
42. C. Deng, R. Ji, W. Liu, X. Gao, and D. Tao, "Visual reranking through weakly supervised multi-graph learning, " in Proc. ICCV, Sydney, NSW, Australia, 2013, pp. 2600-2607.
43. D. Zhang et al., "A unified approximate nearest neighbor search scheme by combining data structure and hashing, " in Proc. IJCAI, Beijing, China, 2013, pp. 681-687.
44. T. Xia, D. Tao, T. Mei, and Y. Zhang, "Multiview spectral embedding, " IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 40, no. 6, pp. 1438-1446, Dec. 2010.
45. Y. Pang, Z. Ji, P. Jing, and X. Li, "Ranking graph embedding for learning to rerank, " IEEE Trans. Neural Netw. Learn. Syst., vol. 24, no. 8, pp. 1292-1303, Aug. 2013.
46. H. Jegou, M. Douze, and C. Schmid, "Product quantization for nearest neighbor search, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 1, pp. 117-128, Jan. 2011.
47. M. Datar, N. Immorlica, P. Indyk, and V. S. Mirrokni, "Locality-sensitive hashing scheme based on p-stable distributions, " in Proc. ACM SOCG, Brooklyn, NY, USA, 2004, pp. 253-262.
48. A. Joly and O. Buisson, "Random maximum margin hashing, " in Proc. CVPR, Providence, RI, USA, 2011, pp. 873-880.
49. J. He, S. Kumar, and S.-F. Chang, "On the difficulty of nearest neighbor search, " in Proc. ICML, Edinburgh, U. K., 2012, pp. 1127-1134.
50. M. Raginsky and S. Lazebnik, "Locality-sensitive binary codes from shift-invariant kernels, " in Proc. NIPS, Vancouver, BC, Canada, 2009, pp. 1509-1517.
51. B. Kulis and T. Darrell, "Learning to hash with binary reconstructive embeddings, " in Proc. NIPS, Vancouver, BC, Canada, 2009, pp. 1042-1050.
52. D. Nister and H. Stewenius, "Scalable recognition with a vocabulary tree, " in Proc. CVPR, New York, NY, USA, 2006, pp. 2161-2168.
53. D. Zhang, F. Wang, and L. Si, "Composite hashing with multiple information sources, " in Proc. ACM SIGIR, Beijing, China, 2011, pp. 225-234.
54. T. Ge, K. He, Q. Ke, and J. Sun, "Optimized product quantization for approximate nearest neighbor search, " in Proc. CVPR, Portland, OR, USA, 2013, pp. 2946-2953.
55. L. Yu, C. Ding, and S. Loscalzo, "Stable feature selection via dense feature groups, " in Proc. ACM SIGKDD, Las Vegas, NV, USA, 2008, pp. 803-811.
56. A. Krizhevsky, "Learning multiple layers of features from tiny images, " Dept. Comput. Sci., University of Toronto, ON, Canada, Tech. Rep., 2009.
57. A. Oliva and A. Torralba, "Modeling the shape of the scene: A holistic representation of the spatial envelope, " Int. J. Comput. Vis., vol. 42, no. 3, pp. 145-175, May 2001.
58. T.-S. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y. Zheng, "NUS-WIDE: A real-world Web image database from National University of Singapore, " in Proc. ACM CIVR, Fira, Greece, 2009, Art. ID 48.
59. M. Norouzi, A. Punjani, and D. J. Fleet, "Fast search in hamming space with multi-index hashing, " in Proc. CVPR, Providence, RI, USA, 2012, pp. 3108-3115.
60. X. Liu, J. He, and B. Lang, "Reciprocal hash tables for nearest neighbor search, " in Proc. AAAI, Bellevue, WA, USA, 2013, pp. 626-632.
61. M. Slaney, Y. Lifshits, and J. He, "Optimal parameters for localitysensitive hashing, " Proc. IEEE, vol. 100, no. 9, pp. 2604-2623, Sep. 2012.