Spherical hashing

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2012, Pages 2957-2964

  Heo, Jae Pil ^a   Lee, Youngwoon ^a   He, Junfeng ^b   Chang, Shih Fu ^b   Yoon, Sung Eui ^a  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

^b Columbia University ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BINARY CODING; CODE DISTANCE; COHERENT DATA; COMPUTER VISION PROBLEMS; DATA POINTS; DATA REPRESENTATIONS; DESCRIPTORS; ENCODING SCHEMES; HASHING FUNCTIONS; HASHING TECHNIQUES; HIGH DIMENSIONAL DATA; HIGH DIMENSIONAL SPACES; HYPER-SPHERES; IMAGE DATABASE; ITERATIVE OPTIMIZATION; NEAREST NEIGHBOR SEARCH; PERFORMANCE GAIN; SIMILARITY SEARCH;

BINARY CODES; ENCODING (SYMBOLS); GEOMETRY; HAMMING DISTANCE; HASH FUNCTIONS; ITERATIVE METHODS; SPHERES;

COMPUTER VISION;

EID: 84866674730     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2012.6248024     Document Type: Conference Paper

References (27)

1. M. S. Charikar. Similarity estimation techniques from rounding algorithms. In STOC, 2002.
2. O. Chum, J. Philbin, and A. Zisserman. Near duplicate image detection: min-hash and tf-idf weighting. In BMVC, 2008.
3. M. Datar, N. Immorlica, P. Indyk, and V. S. Mirrokni. Locality-sensitive hashing scheme based on p-stable distributions. In SoCG, 2004.
4. R. Datta, D. Joshi, J. Li, and J. Z. Wang. Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Survey, 40(2):1-60, 2008.
5. R. F. S. Filho, A. Traina, C. J. Traina., and C. Faloutsos. Similarity search without tears: the omni-family of all-purpose access methods. In Int'l Conf. on Data Engineering, 2001.
6. J. H. Friedman, J. L. Bentley, and R. A. Finkel. An algorithm for finding best matches in logarithmic expected time. ACM TOMS, 3(3):209-226, 1977.
7. Y. Gong and S. Lazebnik. Iterative quantization: a procrustean approach to learning binary codes. In CVPR, 2011.
8. A. Gordo and F. Perronnin. Asymmetric distances for binary embeddings. In CVPR, 2011.
9. L. Greengard. The rapid evaluation of potential fields in particle systems. MIT Press, Cambridge, 1988.
10. J. He, R. Radhakrishnan, S.-F. Chang, and C. Bauer. Compact hashing with joint optimization of search accuracy and time. In CVPR, 2011.
11. P. Indyk and R. Motwani. Approximate nearest neighbors: toward removing the curse of dimensionality. In STOC, 1998.
12. H. V. Jagadish, B. C. Ooi, K.-L. Tan, C. Yu, and R. Zhang. idistance: An adaptive b+-tree based indexing method for nearest neighbor search. ACM T. on Database Systems, 2005.
13. P. Jain, B. Kulis, and K. Grauman. Fast image search for learned metrics. In CVPR, 2008.
14. H. Jégou, M. Douze, and C. Schmid. Product quantization for nearest neighbor search. IEEE TPAMI, 2011.
15. A. Joly and O. Buisson. Random maximum margin hashing. In CVPR, 2011.
16. K. Kim, M. K. Hasan, J.-P. Heo, Y.-W. Tai, and S.-E. Yoon. Probabilistic cost model for nearest neighbor search in image retrieval. Technical report, KAIST, 2012.
17. B. Kulis and K. Grauman. Kernelized locality-sensitive hashing for scalable image search. In ICCV, 2009.
18. D. Nistér and H. Stewénius. Scalable recognition with a vocabulary tree. In CVPR, 2006.
19. A. Oliva and A. Torralba. Modeling the shape of the scene: a holistic representation of the spatial envelope. IJCV, 2001.
20. M. Raginsky and S. Lazebnik. Locality sensitive binary codes from shift-invariant kernels. In NIPS, 2009.
21. J. Sivic and A. Zisserman. Video google: A text retrieval approach to object matching in videos. In ICCV, 2003.
22. K. Terasawa and Y. Tanaka. Spherical lsh for approximate nearest neighbor search on unit hypersphere. In Algorithms and Data Structures, volume 4619, pages 27-38, 2007.
23. A. Torralba, R. Fergus, and Y. Weiss. Small codes and large image databases for recognition. In CVPR, 2008.
24. J. Venkateswaran, D. Lachwani, T. Kahveci, and C. Jermaine. Reference-based indexing of sequence databases. In VLDB, 2006.
25. J. Wang, S. Kumar, and S.-F. Chang. Semi-supervised hashing for scalable image retrieval. In CVPR, 2010.
26. Y. Weiss, A. Torralba, and R. Fergus. Spectral hashing. In NIPS, 2008.
27. A. M. Yaglom and I. M. Yaglom. Challenging Mathematical Problems with Elementary Solutions. New York: Dover Pub., Inc., 1987.