Asymmetric distances for binary embeddings

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 36, Issue 1, 2014, Pages 33-47

  Gordo, Albert ^a   Perronnin, Florent ^b   Gong, Yunchao ^c   Lazebnik, Svetlana ^d  

^a INRIA RHÔNE ALPES   (France)

^b XEROX RESEARCH CENTRE EUROPE   (France)

^c Brooks Computer Science Building   (United States)

^d University of Illinois at Urbana Champaign   (United States)

Author keywords

Asymmetric distances; Binary codes; Large scale retrieval

Indexed keywords

ASYMMETRIC DISTANCES; BINARY EMBEDDING; EMBEDDING ALGORITHMS; EMBEDDING TECHNIQUE; LARGE-SCALE RETRIEVAL; LOCALITY SENSITIVE HASHING; LOCALITY SENSITIVES; SEARCH EFFICIENCY;

BINARY CODES; DATA COMPRESSION; HAMMING DISTANCE; ITERATIVE METHODS;

QUERY PROCESSING;

EID: 84890360780     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2013.101     Document Type: Article

References (41)

1. A. Gordo and F. Perronnin, "Asymmetric Distances for Binary Embeddings," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 729-736, 2011.
2. M. Everingham, L.V. Gool, C. Williams, J. Winn, and A. Zisserman, "The Pascal Visual Object Classes (VOC) Challenge," Int'l J. Computer Vision, vol. 88, no. 2, pp. 303-338, 2010.
3. L. Fei-Fei, R. Fergus, and P. Perona, "One-Shot Learning of Object Categories," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 28, no. 4, pp. 594-611, Apr. 2006. (Pubitemid 43264657)
4. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, "Imagenet: A Large-Scale Hierarchical Image Database," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 248-255, 2009.
5. A. Torralba, R. Fergus, and W. Freeman, "80 Million Tiny Images: A Large Data Set for Non-Parametric Object and Scene Recognition," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 11, pp. 1958-1970, Nov. 2008.
6. 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, pp. 145-175, 2001. (Pubitemid 32680801)
7. J. Sivic and A. Zisserman, "Video Google: A Text Retrieval Approach to Object Matching in Videos," Proc. Ninth IEEE Int'l Conf. Computer Vision, pp. 1470-1477, 2003.
8. G. Csurka, C. Dance, L. Fan, J. Willamowski, and C. Bray, "Visual Categorization with Bags of Keypoints," Proc. Workshop Statistical Learning Computer Vision, 2004.
9. F. Perronnin and C. Dance, "Fisher Kernels on Visual Vocabularies for Image Categorization," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2007.
10. F. Perronnin, J. Sanchez, and T. Mensink, "Improving the Fisher Kernel for Large-Scale Image Classification," Proc. 11th European Conf. Computer Vision, pp. 143-156, 2010.
11. H. Jegou, M. Douze, C. Schmid, and P. Perez, "Aggregating Local Descriptors into a Compact Image Representation," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 3304-3311, 2010.
12. P. Indyk and R. Motwani, "Approximate Nearest Neighbors: Towards Removing the Curse of Dimensionality," Proc. 13th Ann. ACM Symp. Theory Computing (STOC '98), pp. 604-613, 1998.
13. M. Charikar, "Similarity Estimation Techniques from Rounding Algorithms," Proc. 34th Ann. ACM Symp. Theory Computing (STOC '02), pp. 380-388, 2002. (Pubitemid 35009398)
14. M. Raginsky and S. Lazebnik, "Locality-Sensitive Binary Codes from Shift-Invariant Kernels," Proc. Advances in Neural Information Processing, pp. 1509-1517, 2009.
15. Y. Weiss, A. Torralba, and R. Fergus, "Spectral Hashing," Proc. Advances in Neural Information Processing, 2008.
16. B. Kulis and K. Grauman, "Kernelized Locality-Sensitive Hashing for Scalable Image Search," Proc. IEEE Int'l Conf. Computer Vision, pp. 2130-2137, 2009.
17. J. Brandt, "Transform Coding for Fast Approximate Nearest Neighbor Search in High Dimensions," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1815-1822, 2010.
18. J. Wang, S. Kumar, and S.-F. Chang, "Semi-Supervised Hashing for Large Scale Search," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2010.
19. L. Torresani, M. Szummer, and A. Fitzgibbon, "Efficient Object Category Recognition Using Classemes," Proc. 11th European Conf. Computer Vision, pp. 776-789, 2010.
20. A. Bergamo, L. Torresani, and A. Fitzgibbon, "PiCoDes: Learning a Compact Code for Novel-Category Recognition," Proc. Neural Information Processing Systems, pp. 2088-2096, 2011.
21. S. Korman and S. Avidan, "Coherency Sensitive Hashing," Proc. IEEE Int'l Conf. Computer Vision, pp. 1607-1614, 2011.
22. Y. Gong and S. Lazebnik, "Iterative Quantization: A Procrustean Approach to Learning Binary Codes," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 817-824, 2011.
23. M. Norouzi and D. Fleet, "Minimal Loss Hashing for Compact Binary Codes," Proc. Int'l Conf. Machine Learning, 2011.
24. J. Wang, S. Kumar, and S. Chang, "Sequential Projection Learning for Hashing with Compact Codes," Proc. Int'l Conf. Machine Learning, 2011.
25. J.-P. Heo, Y. Lee, J. He, S.-F. Chang, and S. eui Yoon, "Spherical Hashing," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 2957-2964, 2012.
26. C. Strecha, A.M. Bronstein, M.M. Bronstein, and P. Fua, "LDAHash: Improved Matching with Smaller Descriptors," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 34, no. 1, pp. 66-78, Jan. 2012.
27. M. Norouzi, R. Salakhutdinov, and D. Fleet, "Hamming Distance Metric Learning," Proc. Advances in Neural Information Processing Systems, pp. 1070-1078, 2012.
28. Y. Gong, S. Kumar, V. Verma, and S. Lazebnik, "Angular Quantization Based Binary Codes for Fast Similarity Search," Proc. Advances in Neural Information Processing Systems, pp. 1205-1213, 2012.
29. W. Liu, J. Wang, R. Ji, Y.-G. Jiang, and S.-F. Chang, "Supervised Hashing with Kernels," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 2074-2081, 2012.
30. Y. Weiss, R. Fergus, and A. Torralba, "Multidimensional Spectral Hashing," Proc. 12th European Conf. Computer Vision (ECCV '12), pp. 340-353, 2012.
31. W. Dong, M. Charikar, and K. Li, "Asymmetric Distance Estimation with Sketches for Similarity Search in High-Dimensional Spaces," Proc. 31st Ann. Int'l ACM SIGIR Conf. Research Development Information Retrieval (SIGIR '08), 2008.
32. H. Jegou, M. Douze, and C. Schmid, "Product Quantization for Nearest Neighbor Search," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 33, no. 1, pp. 117-128, Jan. 2010.
33. A. Rahimi and B. Recht, "Random Features for Large-Scale Kernel Machines," Proc. Conf. Advances in Neural Information Processing Systems, 2007.
34. H. Jegou, M. Douze, and C. Schmid, "Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search," Proc. 10th European Conf. Computer Vision, pp. 304-317, http://lear.inrialpes.fr/~jegou/data.php, 2008.
35. P. Schonemann, "A Generalized Solution of the Orthogonal Procrustres Problem," Psychometrika, vol. 31, pp. 1-10, 1966.
36. A. Krizhevsky, "Learning Multiple Layers of Features from Tiny Images," technical report, Univ. of Toronto, 2009.
37. G. Griffin, A. Holub, and P. Perona, "Caltech-256 Object Category Data Set," technical report, California Inst. of Technology, 2007.
38. D. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," Int'l J. Computer Vision, vol. 60, pp. 91-110, 2004.
39. F. Perronnin, Y. Liu, J. Sanchez, and H. Poirier, "Large-Scale Image Retrieval with Compressed Fisher Vectors," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 3384-3391, 2010.
40. D. Nister and H. Stewenius, "Scalable Recognition with a Vocabulary Tree," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 2161-2168, 2006. (Pubitemid 44931581)
41. H. Jegou and O. Chum, "Negative Evidences and Co-Occurrences in Image Retrieval: The Benefit of PCA and Whitening," Proc. 12th European Conf. Computer Vision (ECCV '12), pp. 774-787, 2012.