Thick boundaries in binary space and their influence on nearest-neighbor search

Pattern Recognition Letters

Volumn 33, Issue 16, 2012, Pages 2173-2180

  Trzcinski, Tomasz ^a   Lepetit, Vincent ^a   Fua, Pascal ^a  

^a EPFL   (Switzerland)

Author keywords

Approximate nearest neighbor search; Binary vectors; Hierarchical k means; Locality sensitive hashing

Indexed keywords

ANN ALGORITHM; APPROXIMATE NEAREST NEIGHBOR; APPROXIMATE NEAREST NEIGHBOR SEARCH; BINARIZE; BINARY VECTORS; CLUSTER CENTERS; COMPUTATIONAL COSTS; DESCRIPTORS; FLOATING POINT NUMBERS; FLOATING POINTS; K-MEANS; LARGE DATABASE; LINEAR SEARCH; LOCALITY SENSITIVE HASHING; NEAREST NEIGHBOR SEARCH; RANDOM POINTS; SIMILARITY COMPUTATION; STATE-OF-THE-ART ALGORITHMS; TREE-BASED ALGORITHMS; VORONOI DIAGRAMS;

DIGITAL ARITHMETIC; IMAGE RETRIEVAL; TREES (MATHEMATICS); VECTORS;

CLUSTERING ALGORITHMS;

EID: 84866552281     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2012.08.006     Document Type: Article

References (30)

1. Y. Amit, D. Geman, and B. Jedynak Efficient focusing and face detection Face Recognition: From Theory to Applications 1998 143 158
2. A. Andoni, and P. Indyk Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions Commun. ACM 51 1 2008 117 122
3. S. Arya, D. Mount, N. Netanyahu, R. Silverman, and A. Wu An optimal algorithm for approximate nearest neighbor searching fixed dimensions J. ACM 45 1998 891 923
4. H. Bay, T. Tuytelaars, and L. Van Gool SURF: speeded up robust features Eur. Conf. Computer Vision. 2006 404 417 (Pubitemid 44029795)
5. J. Beis, and D. Lowe Shape indexing using approximate nearest-neighbour search in high-dimensional spaces Conf. on Computer Vision and Pattern Recognition 1997 1000 1006
6. M. Brown, G. Hua, and S. Winder Discriminative Learning of Local Image Descriptors IEEE Trans. Pattern Anal. Machine Intell. 33 1 2011 43 57
7. Calonder, M.; Lepetit, V.; Strecha, C.; Fua, P.; 2010. BRIEF: Binary Robust Independent Elementary Features. In: Eur. Conf. Computer Vision. Heraklion, Greece.
8. Cha, S.-H.; Srihari, S.; 2000. Nearest neighbor search using additive binary tree. In: Conference on Computer Vision and Pattern Recognition.
9. M. Charikar Similarity estimation techniques from rounding algorithms Proc. 34th Ann. ACM Sympos. Theory Comput. 2002 380 388 (Pubitemid 35009398)
10. J. Friedman, J. Bentley, and R. Finkel An algorithm for finding best matches in logarithmic expected time ACM Trans. Math. Software 3 3 1977 209 226
11. K. Fukunaga, and P. Narendra A branch and bound algorithm for computing k-nearest neighbors IEEE Trans. Comput. 24 1975 750 753
12. Gionis, A.; Indik, P.; Motwani, R.; 1999. Similarity search in high dimensions via Hashing. In: International Conference on Very Large Databases.
13. Gong, Y.; Lazebnik, S.; 2011. Iterative quantization: a procrustean approach to learning binary codes. In: Conference on Computer Vision and Pattern Recognition.
14. R. Hartley, and A. Zisserman Multiple View Geometry in Computer Vision 2000 Cambridge University Press
15. Indyk, P.; Motwani, R.; 1998. Approximate nearest neighbors: towards removing the curse of dimensionality. In: Proceedings of the 30th Symposium on Theory of Computing, pp. 604-613.
16. B. Kulis, and T. Darrell Learning to hash with binary reconstructive embeddings Adv. Neural Informat. Proc. Systems 2009 1042 1050
17. T. Liu, A. Moore, A. Gray, and K. Yang An investigation of practical approximate nearest neighbor algorithm Advance in Neural Information Processing Systems 2004
18. D. Lowe Distinctive image features from scale-invariant keypoints Internat. J. Computer Vision 20 2 2004 91 110
19. K. Mikolajczyk, C. Schmid, and A. Zisserman Human Detection Based on a Probabilistic Assembly of Robust Part Detectors Eur. Conf. Computer Vision 2004 69 81
20. M. Miller, M. Rodriguez, and I. Cox Audio fingerprinting: nearest neighbor search in high dimensional binary spaces J. VLSI Signal Process. Systems 41 3 2005 285 291 (Pubitemid 43005842)
21. Muja, M.; Lowe, D.; 2009. Fast approximate nearest neighbors with automatic algorithm configuration. In: International Conference on Computer Vision.
22. Nister, D.; Stewenius, H.; 2006. Scalable recognition with a vocabulary tree. In: Conference on Computer Vision and Pattern Recognition.
23. M. Raginsky, and S. Lazebnik Locality-sensitive binary codes from shift-invariant kernels Adv. Neural Inform. Proc. Syst. 2009 1509 1517
24. R. Salakhutdinov, and G. Hinton Semantic hashing Internat. J. Approx. Reason. 50 7 2009 969 978
25. Shakhnarovich, G.; 2005. Learning Task-Specific Similarity, Ph.D. thesis, Massachusetts Institute of Technology.
26. Silpa-Anan, C.; Hartley, R.; 2008. Optimised kd-trees for fast image descriptor matching. In: Conference on Computer Vision and Pattern Recognition.
27. Stirling, J.; 1764. Methodus Differentialis [electronic Resource]: Sive Tractatus De Summatione Et Interpolatione Serierum Infinitarum, J. Whiston and B. White.
28. C. Strecha, A. Bronstein, M. Bronstein, and P. Fua LDAHash: improved matching with smaller descriptors IEEE Trans. Pattern Anal. Mach. Intell. 34 2012
29. Y. Weiss, A. Torralba, and R. Fergus Spectral hashing Adv. Neural Inform. Process. Systems 21 2009 1753 1760
30. Yianilos, P.; 1993. Data structures and algorithms for nearest neighbor search in general metric spaces. In: Fourth ACM-SIAM Symposium on Discrete Algorithms, 1993.