126
Views
0
CrossRef citations to date
0
Altmetric
Original Articles

Locality preserving hashing for fast image search: theory and applications

, &
Pages 349-359 | Received 04 Jun 2015, Accepted 30 Dec 2015, Published online: 10 Mar 2016

References

  • Bronstein, M. M., Bronstein, A. M., Michel, F., & Paragios, N. (2010). Data fusion through cross-modality metric learning using similarity-sensitive hashing. CVPR, pp. 3594–3601.
  • Dong, W., Wang, Z., Josephson, W., Charikar, M., & Li, K. (2008). Modeling LSH for performance tuning. Proc. CIKM, pp. 669–678.
  • Fan, R., Chang, K., Hsieh, C., Wang, X., & Lin, C. (2008). LIBLINEAR: A library for large linear classification. Journal of Machine Learning Research, 9, 1871–1874.
  • Gionis, A., Indyk, P., & Motwani, R. (1999). Similarity search in high dimensions via hashing. Proc. International Conference on Very Large Data Bases, pp. 518–529.
  • Gong, Y., & Lazebnik, S. (2011). Iterative quantization: A procrustean approach to learning binary codes. CVPR, pp. 817–824.
  • He, J., Liu, W., & Chang, S. (2010). Scalable similarity search with optimized kernel hashing. Proc. SIGKDD, pp. 1129–1138.
  • He, J., Chang, S., Radhakrishnan, R., & Bauer, C. (2011). Compact hashing with joint optimization of search accuracy and time. Proc. CVPR, pp. 753–760.
  • Huang, Y., & Long, Y. (2006). Super-resolution using neural networks based on the optimal recovery theory. Journal of Computational Electronics, 5, 275–281.
  • Indyk, P., Motwani, R., Raghavan, P., & Vempala, S. (1997). Locality-preserving hashing in multidimensional spaces. Proc. STOC, pp. 618–625.
  • Jain, P., Kulis, B., & Grauman, K. (2008). Fast image search for learned metrics, Proc. CVPR, pp. 1–8.
  • Joly, A., & Buisson, O. (2011). Random maximum margin hashing. Proc. CVPR, pp. 873–880.
  • Korman, S., & Avidan, S. (2011). Coherency sensitive hashing. Proc. ICCV, pp. 1607–1614.
  • Kulis, B., & Grauman, K. (2009). Kernelized locality-sensitive hashing for scalable image search. Proc. ICCV, pp. 2130–2137.
  • Liu, W., Wang, J., Kumar, S., & Chang, S. F. (2011). Hashing with graphs. Proc. ICML, pp. 1–8.
  • Long, Y., & Huang, Y. (2006). Image based source camera identification using demosaicking. Proceedings of IEEE 8th Workshop on Multimedia Signal Processing, Victoria, Canada, pp. 419–424.
  • Lv, Q., Josephson, W., Wang, Z., Charikar, M., & Li, K. (2007). Multi-probe LSH: Efficient indexing for high-dimensional similarity search. Proc. International Conference on Very Large Data Bases, pp. 950–961.
  • Macskassy, S. A., Hirsh, H., Banerjee, A., & Dayanik, A. A. (2003). Converting numerical classification into text classification. Artificial Intelligence, 143(1), 51–77.10.1016/S0004-3702(02)00359-4
  • Mu, Y., Shen, J., & Yan, S. (2010). Weakly-supervised hashing in kernel space. Proc. CVPR, pp. 3344–3351.
  • Raginsky, M., & Lazebnik, S. (2009). Locality-sensitive binary codes from shift-invariant kernels. Proc. NIPS, pp. 1509–1517.
  • Shakhnarovich, G., Viola, P., & Darrell, T. (2003). Fast pose estimation with parameter-sensitive hashing. Proc. ICCV, pp. 750–757.
  • Torralba, A., Fergus, R., & Weiss, Y. (2008). Small codes and large databases for recognition. Proc. CVPR, pp. 1–8.
  • Wang, J., Kumar, S., & Chang, S. F. (2010a). Semi-supervised hashing for scalable image retrieval. Proc. CVPR, pp. 3424–3431.
  • Wang, J., Kumar, S., & Chang, S. F. (2010b). Sequential projection learning for hashing with compact codes. Proc. ICML, pp. 1127–1134.
  • Weiss, Y., Torralba, A., & Fergus, R. (2009). Spectral hashing. Proc. NIPS, pp. 1753–1760.
  • Weiss, Y., Fergus, R., & Torralba, A. (2012). Multidimensional spectral hashing. ECCV, pp. 340–353.
  • Xu, H., Wang, J., Li, Z., Zeng, G., Li, S., & Yu, N. (2011). Complementary hashing for approximate nearest neighbor search. Proc. ICCV, pp. 1631–1638.
  • Yu, X., Zhang, S. T., Liu, B., & Zhong, L. (2013). Large scale medical image search via unsupervised PCA hashing. Proc. CVPR Workshop, pp. 393–398.
  • Zhang, D., Wang, J., Cai, D., & Lu, J. (2010). Self-taught hashing for fast similarity search. Proc. SIGIR, pp. 18–25.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.