Semi-supervised hashing for large-scale search

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 34, Issue 12, 2012, Pages 2393-2406

  Wang, Jun ^a   Kumar, Sanjiv ^b   Chang, Shih Fu ^c  

^a IBM T J WATSON RESEARCH CENTER   (United States)

^b GOOGLE INC   (United States)

^c Howard Hughes Medical Institute   (United States)

Author keywords

Binary codes; Hashing; Nearest neighbor search; Pairwise labels; Semi supervised hashing; Sequential hashing

Indexed keywords

APPROXIMATE NEAREST NEIGHBOR; EMPIRICAL ERRORS; HASHING; HASHING METHOD; HASHING TECHNIQUES; LABELED DATA; LARGE DATASETS; LOCALITY SENSITIVE HASHING; MEMORY EFFICIENCY; NEAREST NEIGHBOR SEARCH; NON-ORTHOGONAL; OVERFITTING; REGULARIZER; SEMANTIC SIMILARITY; SEMI-SUPERVISED; SEQUENTIAL HASHING; SEQUENTIAL LEARNING;

BINARY CODES; HASH FUNCTIONS; IMAGE RETRIEVAL; INFORMATION THEORY; INTERNET PROTOCOLS;

COMPUTATIONAL EFFICIENCY;

EID: 84865410773     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2012.48     Document Type: Article

References (40)

1. R. Datta, D. Joshi, J. Li, and J.Z. Wang, "Image Retrieval: Ideas, Influences, and Trends of the New Age," ACM Computing Surveys, vol. 40, no. 2, pp. 1-60, 2008.
2. G. Shakhnarovich, T. Darrell, and P. Indyk, Nearest-Neighbor Methods in Learning and Vision: Theory and Practice. MIT Press, 2006.
3. P. Indyk and R. Motwani, "Approximate Nearest Neighbors: Towards Removing the Curse of Dimensionality," Proc. 30th ACM Symp. Theory of Computing, pp. 604-613, 1998.
4. J. Bentley, "Multidimensional Binary Search Trees Used for Associative Searching," Comm. ACM, vol. 18, no. 9, pp. 509-517, 1975.
5. J.H. Friedman, J.L. Bentley, and R.A. Finkel, "An Algorithm for Finding Best Matches in Logarithmic Expected Time," ACM Trans. Math. Software, vol. 3, no. 3, pp. 209-226, 1977.
6. C. Silpa-Anan and R. Hartley, "Optimised Kd-Trees for Fast Image Descriptor Matching," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2008.
7. S. Omohundro, "Efficient Algorithms with Neural Network Behavior," Complex Systems, vol. 1, no. 2, pp. 273-347, 1987.
8. J. Uhlmann, "Satisfying General Proximity/Similarity Queries with Metric Trees," Information Processing Letters, vol. 40, no. 4, pp. 175-179, 1991.
9. P. Yianilos, "Data Structures and Algorithms for Nearest Neighbor Search in General Metric Spaces," Proc. Fourth Ann. ACM-SIAM Symp. Discrete Algorithms, pp. 311-321, 1993. (Pubitemid 23612715)
10. M. Muja and D.G. Lowe, "Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration," Proc. Int'l Conf. Computer Vision Theory and Applications, pp. 331-340, 2009.
11. P. Indyk, "Nearest-Neighbor Searching in High Dimensions," Handbook of Discrete and Computational Geometry, J.E. Goodman and J. O'Rourke, eds., CRC Press LLC, 2004.
12. A. Gionis, P. Indyk, and R. Motwani, "Similarity Search in High Dimensions via Hashing," Proc. 25th Int'l Conf. Very Large Data Bases, pp. 518-529, 1999.
13. Y. Weiss, A. Torralba, and R. Fergus, "Spectral Hashing," Proc. Advances in Neural Information Processing Systems, D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, eds., vol. 21, pp. 1753-1760, 2008.
14. M. Raginsky and S. Lazebnik, "Locality-Sensitive Binary Codes from Shift-Invariant Kernels," Proc. Advances in Neural Information Processing Systems 22, Y. Bengio, D. Schuurmans, J. Lafferty, C.K.I. Williams, and A. Culotta, eds., pp. 1509-1517, 2009.
15. B. Kulis and K. Grauman, "Kernelized Locality-Sensitive Hashing for Scalable Image Search," Proc. IEEE Int'l Conf. Computer Vision, pp. 2130-2137, 2009.
16. A. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, "Content-Based Image Retrieval at the End of the Early Years," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 12, pp. 1349-1380, Dec. 2000. (Pubitemid 32088465)
17. B. Kulis, P. Jain, and K. Grauman, "Fast Similarity Search for Learned Metrics," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 31, no. 12, pp. 2143-2157, Dec. 2009.
18. G. Shakhnarovich, "Learning Task-Specific Similarity," PhD dissertation, Massachusetts Inst. of Technology, 2005.
19. G. Hinton and R. Salakhutdinov, "Reducing the Dimensionality of Data with Neural Networks," Science, vol. 313, no. 5786, pp. 504- 507, 2006. (Pubitemid 44148451)
20. B. Kulis and T. Darrell, "Learning to Hash with Binary Reconstructive Embeddings," Proc. Advances in Neural Information Processing Systems, Y. Bengio, D. Schuurmans, J. Lafferty, C.K.I. Williams, and A. Culotta, eds., vol. 20, pp. 1042-1050, 2009.
21. Y. Mu, J. Shen, and S. Yan, "Weakly-Supervised Hashing in Kernel Space," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 3344-3351, June 2010.
22. A. Torralba, R. Fergus, and Y. Weiss, "Small Codes and Large Image Databases for Recognition," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2008.
23. M. Datar, N. Immorlica, P. Indyk, and V. Mirrokni, "Locality- Sensitive Hashing Scheme Based on P-Stable Distributions," Proc. 12th Ann. Symp. Computational Geometry, pp. 253-262, 2004.
24. M. Bawa, T. Condie, and P. Ganesan, "LSH Forest: Self-Tuning Indexes for Similarity Search," Proc. 14th Int'l Conf. World Wide Web, pp. 651-660, 2005.
25. Q. Lv, W. Josephson, Z. Wang, M. Charikar, and K. Li, "Multi- Probe LSH: Efficient Indexing for High-Dimensional Similarity Search," Proc. 33rd Int'l Conf. Very Large Data Bases, pp. 950-961, 2007.
26. L. Cayton and S. Dasgupta, "A Learning Framework for Nearest Neighbor Search," Proc. Advances in Neural Information Processing Systems 20, J. Platt, D. Koller, Y. Singer, and S. Roweis, eds., pp. 233-240, 2008.
27. J. Wang, S. Kumar, and S.-F. Chang, "Sequential Projection Learning for Hashing with Compact Codes," Proc. 27th Int'l Conf. Machine Learning, J. Fürnkranz and T. Joachims, eds., pp. 1127- 1134, June 2010.
28. Y. Freund and R. Schapire, "A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting," Proc. Second European Conf. Computational Learning Theory, pp. 23-37, 1995.
29. C. Fowlkes, S. Belongie, F. Chung, and J. Malik, "Spectral Grouping Using the Nystrom Method," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 2, pp. 214-225, Feb. 2004.
30. S. Baluja and M. Covell, "Learning to Hash: Forgiving Hash Functions and Applications," Data Mining and Knowledge Discovery, vol. 17, no. 3, pp. 402-430, 2008.
31. A. Torralba, R. Fergus, and W. Freeman, "80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 11, pp. 1958-1970, Nov. 2008.
32. A. Oliva and A. Torralba, "Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope," Int'l J. Computer Vision, vol. 42, no. 3, pp. 145-175, 2001. (Pubitemid 32680801)
33. T.-S. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y.-T. Zheng, "Nus- Wide: A Real-World Web Image Database from National University of Singapore," Proc. ACM Conf. Image and Video Retrieval, July 2009.
34. D.G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," Int'l J. Computer Vision, vol. 60, no. 2, pp. 91-110, 2004.
35. Y.-G. Jiang, C.-W. Ngo, and J. Yang, "Towards Optimal Bag-of- Features for Object Categorization and Semantic Video Retrieval," Proc. Sixth ACM Int'l Conf. Image and Video Retrieval, pp. 494-501, 2007. (Pubitemid 350229664)
36. J. Wang, S. Kumar, and S.-F. Chang, "Semi-Supervised Hashing for Scalable Image Retrieval," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 3424-3431, June 2010.
37. R. Fergus, Y. Weiss, and A. Torralba, "Semi-Supervised Learning in Gigantic Image Collections," Proc. Advances in Neural Information Processing Systems 22, Y. Bengio, D. Schuurmans, J. Lafferty, C.K.I. Williams, and A. Culotta, eds., pp. 522-530, 2009.
38. R. Schapire and Y. Singer, "Boostexter: A Boosting-Based System for Text Categorization," Machine Learning, vol. 39, no. 2, pp. 135- 168, 2000. (Pubitemid 30594821)
39. W. Liu, J. Wang, S. Kumar, and S.-F. Chang, "Hashing with Graphs," Proc. 28th Int'l Conf. Machine Learning, June 2011.
40. W. Liu, J. Wang, R. Ji, Y. Jiang, and S.-F. Chang, "Supervised Hashing with Kernels," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 2074-2081, June 2012.