OSRI: A rotationally invariant binary descriptor

IEEE Transactions on Image Processing

Volumn 23, Issue 7, 2014, Pages 2983-2995

  Xu, Xianwei ^a   Tian, Lu ^a   Feng, Jianjiang ^a   Zhou, Jie ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

Binary descriptor; feature matching; local order pattern; real time matching; rotation invariant

Indexed keywords

DIGITAL ARITHMETIC;

DESCRIPTORS; FEATURE MATCHING; LOCAL ORDER; REAL-TIME MATCHING; ROTATION INVARIANT;

PIXELS;

EID: 84902162415     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2014.2324824     Document Type: Article

References (48)

1. A. R. Zamir and M. Shah, "Accurate image localization based on Google maps street view," in Proc. Eur. Conf. Comput. Vis., 2010, pp. 255-268.
2. N. Snavely, S. M. Seitz, and R. Szeliski, "Photo tourism: Exploring photo collections in 3D," ACM Trans. Graph., vol. 25, no. 3, pp. 835-846, 2006.
3. S. Agarwal, N. Snavely, I. Simon, S. M. Seitz, and R. Szeliski, "Building Rome in a day," in Proc. 12th IEEE Int. Conf. Comput. Vis., Sep. /Oct. 2009, pp. 72-79.
4. S. Zhang, Q. Tian, K. Lu, Q. Huang, and W. Gao, "Edge-SIFT: Discriminative binary descriptor for scalable partial-duplicate mobile search," IEEE Trans. Image Process., vol. 18, no. 8, pp. 799-813, Jul. 2013.
5. D. Nistér and H. Stewénius, "Scalable recognition with a vocabulary tree," in Proc. IEEE Conf. CVPR, Jul. 2006, pp. 2161-2168.
6. G. Takacs et al., "Outdoors augmented reality on mobile phone using loxel-based visual feature organization," in Proc. ACM Int. Conf. Multimedia Inform. Retr., Oct. 2008, pp. 427-434.
7. M. Brown and D. G. Lowe, "Automatic panoramic image stitching using invariant features," Int. J. Comput. Vis., vol. 74, no. 1, pp. 59-73, 2007.
8. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Comput. Vis., vol. 60, no. 2, pp. 91-110, 2004.
9. K. Mikolajczyk and C. Schmid, "A performance evaluation of local descriptors," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 10, pp. 1615-1630, Oct. 2005.
10. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool, "Speeded-up robust features (SURF)," Comput. Vis. Image Understand., vol. 110, no. 3, pp. 346-359, 2008.
11. E. Tola, V. Lepetit, and P. Fua, "DAISY: An Efficient dense descriptor applied to wide-baseline stereo," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 5, pp. 815-830, May 2010.
12. B. Fan, F. Wu, and Z. Hu, "Rotationally invariant descriptors using intensity order pooling," IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 10, pp. 2031-2045, Oct. 2012.
13. G. Hua, M. Brown, and S. Winder, "Discriminant embedding for local image descriptors," in Proc. 11th IEEE Int. Conf. Comput. Vis., Oct. 2007, pp. 1-8.
14. T. Tuytelaars and C. Schmid, "Vector quantizing feature space with a regular lattice," in Proc. 11th IEEE Int. Conf. Comput. Vis., Oct. 2007, pp. 1-8.
15. S. Winder, G. Hua, and M. Brown, "Picking the best DAISY," in Proc. IEEE Conf. CVPR, Jun. 2009, pp. 178-185.
16. V. Chandrasekhar, G. Takacs, D. Chen, S. Tsai, R. Grzeszczuk, and B. Girod, "CHoG: Compressed histogram of gradients a low bit-rate feature descriptor," in Proc. IEEE Conf. CVPR, Jun. 2009, pp. 2504-2511.
17. H. Jegou, M. Douze, C. Schmid, and P. Pérez, "Aggregating local descriptors into a compact image representation," in Proc. IEEE Conf. CVPR, Jun. 2010, pp. 3304-3311.
18. M. Brown, G. Hua, and S. Winder, "Discriminative learning of local image descriptors," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 1, pp. 43-57, Jan. 2011.
19. H. Jégou, M. Douze, and C. Schmid, "Product quantization for nearest neighbor search," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 1, pp. 117-128, Jan. 2011.
20. J. He et al., "Mobile product search with bag of hash bits and boundary reranking," in Proc. IEEE Conf. CVPR, Jun. 2012, pp. 3005-3012.
21. G. Shakhnarovich, "Learning task-specific similarity," Ph. D. dissertation, Dept. Elect. Eng. Comput. Sci., Massachusetts Inst. Technol., Cambridge, MA, USA, 2005.
22. A. Torralba, R. Fergus, and Y. Weiss, "Small codes and large image databases for recognition," in Proc. IEEE Conf. CVPR, Jun. 2008, pp. 1-8.
23. H. Jégou, M. Douze, and C. Schmid, "Improving bag-of-features for large scale image search," Int. J. Comput. Vis., vol. 87, no. 3, pp. 316-336, 2010.
24. C. Strecha, A. M. Bronstein, M. M. Bronstein, and P. Fua, "LDAHash: Improved matching with smaller descriptors," IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 1, pp. 66-78, Jan. 2012.
25. K. He, F. Wen, and J. Sun, "K-means hashing: An affinity-preserving quantization method for learning binary compact codes," in Proc. IEEE Conf. CVPR, Jun. 2013, pp. 2938-2945.
26. X. Li, C. Shen, A. Dick, and A. van den Hengel, "Learning compact binary codes for visual tracking," in Proc. IEEE Conf. CVPR, Jun. 2013, pp. 2419-2426.
27. Y. Gong, S. Kumar, H. A. Rowley, and S. Lazebnik, "Learning binary codes for high-dimensional data using bilinear projections," in Proc. IEEE Conf. CVPR, Jun. 2013, pp. 484-491.
28. M. Calonder, V. Lepetit, M. Özuysal, T. Trzcinski, C. Strecha, and P. Fua, "BRIEF: Computing a local binary descriptor very fast," IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 7, pp. 1281-1298, Jul. 2012.
29. E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, "ORB: An efficient alternative to SIFT or SURF," in Proc. IEEE Int. Conf. Comput. Vis., Nov. 2011, pp. 2564-2571.
30. S. Leutenegger, M. Chli, and R. Y. Siegwart, "BRISK: Binary robust invariant scalable keypoints," in Proc. IEEE Int. Conf. Comput. Vis., Nov. 2011, pp. 2548-2555.
31. A. Alahi, R. Ortiz, and P. Vandergheynst, "FREAK: Fast retina keypoint," in Proc. IEEE Conf. CVPR, Jun. 2012, pp. 510-517.
32. A. Gionis, P. Indyk, and R. Motwani, "Similarity search in high dimensions via hashing," in Proc. Int. Conf. VLDB, Sep. 1999, pp. 518-529.
33. M. Bawa, T. Condie, and P. Ganesan, "LSH forest: Self-tuning indexes for similarity search," in Proc. 14th Int. Conf. WWW, May 2005, pp. 651-660.
34. A. Andoni and P. Indyk, "Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions," Commun. ACM, vol. 51, no. 1, pp. 117-122, 2008.
35. M. Raginsky and S. Lazebnik, "Locality-sensitive binary codes from shift-invariant kernels," in Proc. Adv. NIPS, 2009, pp. 1509-1517.
36. B. Kulis and T. Darrell, "Learning to hash with binary reconstructive embeddings," in Proc. Adv. NIPS, 2009, pp. 1042-1050.
37. R. Salakhutdinov and G. E. Hinton, "Learning a nonlinear embedding by preserving class neighbourhood structure," in Proc. Int. Conf. Artif. Intell. Statist., 2007, pp. 412-419.
38. Y. Gong and S. Lazebnik, "Iterative quantization: A procrustean approach to learning binary codes," in Proc. IEEE Conf. CVPR, Jun. 2011, pp. 817-824.
39. T. Trzcinski and V. Lepetit, "Efficient discriminative projections for compact binary descriptors," in Proc. Eur. Conf. Comput. Vis., 2012, pp. 228-242.
40. T. Trzcinski, M. Christoudias, V. Lepetit, and P. Fua, "Learning image descriptors with the boosting-trick," in Proc. Adv. NIPS, 2012, pp. 278-286.
41. T. Trzcinski, M. Christoudias, P. Fua, and V. Lepetit, "Boosting binary keypoint descriptors," in Proc. IEEE Conf. CVPR, Jun. 2013, pp. 2874-2881.
42. K. Mikolajczyk and C. Schmid, "Scale & affine invariant interest point detectors," Int. J. Comput. Vis., vol. 60, no. 1, pp. 63-86, 2004.
43. H. Cheng, Z. Liu, N. Zheng, and J. Yang, "A deformable local image descriptor," in Proc. IEEE Conf. CVPR, 2008, pp. 1-8.
44. M.-K. Hu, "Visual pattern recognition by moment invariants," IRE Trans. Inform. Theory, vol. 8, no. 2, pp. 179-187, Feb. 1962.
45. P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," in Proc. IEEE Conf. CVPR, Dec. 2001, pp. 511-518.
46. K. Mikolajczyk et al., "A comparison of affine region detectors," Int. J. Comput. Vis., vol. 65, nos. 1-2, pp. 43-72, 2005.
47. A. Vedaldi, "An open implementation of the SIFT detector and descriptor," Dept. Comput. Sci., UCLA, Los Angeles, CA, USA, Tech. Rep. 070012, 2007.
48. J. Heinly, E. Dunn, and J. M. Frahm, "Comparative evaluation of binary features," in Proc. Eur. Conf. Comput. Vis., 2012, pp. 759-773.