Co-transduction for shape retrieval

IEEE Transactions on Image Processing

Volumn 21, Issue 5, 2012, Pages 2747-2757

  Bai, Xiang ^a   Wang, Bo ^b   Yao, Cong ^a   Liu, Wenyu ^a   Tu, Zhuowen ^c,d  

^a HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b UNIVERSITY OF TORONTO   (Canada)

^c MICROSOFT RESEARCH ASIA   (China)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Graph transduction; object retrieval; shape retrieval; similarity measure

Indexed keywords

CO-TRAINING ALGORITHM; DATA SETS; GRAPH TRANSDUCTION; INTRA-CLASS VARIATION; MULTIPLE INPUTS; OBJECT RETRIEVAL; OBJECT SHAPE; RE-RANKING; RETRIEVAL ALGORITHMS; RETRIEVAL SYSTEMS; SEMI-SUPERVISED LEARNING; SHAPE RETRIEVAL; SIMILARITY MEASURE; STATE-OF-THE-ART PERFORMANCE;

LEARNING ALGORITHMS; MOTION PICTURE EXPERTS GROUP STANDARDS;

BACTERIOPHAGES;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84860159759     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2011.2170082     Document Type: Article

References (59)

1. M. Hu, "Visual pattern recognition by moment invariants," IRE Trans. Inf. Theory, vol. 8, no. 2, pp. 179-187, Feb. 1962.
2. C. Zahn and R. Roskies, "Fourier descriptors for plane closed curves," IEEE Trans. Comput., vol. C-21, no. 3, pp. 269-281, Mar. 1972.
3. S. Belongie, J. Malik, and J. Puzicha, "Shape matching and object recognition using shape contexts," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 4, pp. 509-522, Apr. 2002.
4. H. Ling and D. Jacobs, "Shape classification using the inner-distance," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 2, pp. 286-299, Feb. 2007.
5. H. Chui and A. Rangarajan, "A new point matching algorithm for nonrigid registration," Comput. Vis. Image Understand., vol. 89, no. 2/3, pp. 114-141, Mar. 2003.
6. K. Siddiqi, A. Shokoufandeh, S. Dickinson, and S. Zucker, "Shock graph and shape matching," Int. J. Comput. Vis., vol. 35, no. 1, pp. 13-32, Nov. 1999.
7. C. Grigorescu and N. Petkov, "Distance sets for shape filters and shape recognition," IEEE Trans. Image Process., vol. 12, no. 10, pp. 1274-1286, Oct. 2003.
8. R. Gopalan, P. K. Turaga, and R. Chellappa, "Articulation-invariant representation of non-planar shapes," in Proc. ECCV, 2010, pp. 286-299.
9. X. Bai, X. Yang, L. Latecki, W. Liu, and Z. Tu, "Learning context sensitive shape similarity by graph transduction," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 5, pp. 861-874, May 2010.
10. L. Latecki, R. Lakámper, and U. Eckhardt, "Shape descriptors for nonrigid shapes with a single closed contour," in Proc. CVPR, 2000, pp. 424-429.
11. T. B. Sebastian, P. N. Klein, and B. B. Kimia, "Recognition of shapes by editing their shock graphs," IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 5, pp. 550-571, May 2004.
12. X. Zhu, "Semi-supervised learning with graphs," Ph.D. dissertation, Carnegie Mellon Univ., Pittsburgh, PA, 2005, CMU-LTI-05-192.
13. P. Kontschieder,M. Donoser, and H. Bischof, "Beyond pairwise shape similarity analysis," in Proc. ACCV, 2009, pp. 655-666.
14. X. Yang, S. Koknar-Tezel, and L. Latecki, "Locally constrained diffusion process on locally densified distance spaces with applications to shape retrieval," in Proc. CVPR, 2009, pp. 357-364.
15. A. Egozi, Y. Keller, and H. Guterman, "Improving shape retrieval by spectral matching and meta similarity," IEEE Trans. Image Process., vol. 19, no. 5, pp. 1319-1327, May 2010.
16. H. Jegou, C. Schmid, H. Harzallah, and J. Verbeek, "Accurate image search using the contextual dissimilarity measure," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 1, pp. 2-11, Jan. 2010.
17. H. Ling, X. Yang, and L. Latecki, "Balancing deformability and discriminability for shape matching," in Proc. ECCV, 2010, pp. 411-424.
18. A. Temlyakov, B.Munsell, J.Waggoner, and S.Wang, "Two perceptually motivated strategies for shape classification," in Proc. CVPR, 2010, pp. 2289-2296.
19. H. B. Mitchell, Multi-Sensor Data Fusion? An Introduction. Berlin, Germany: Springer-Verlag, 2007.
20. S. Das, High-Level Data Fusion. Norwood, MA: Artech House, 2008.
21. E. P. Xing, A. Y. Ng, M. I. Jordan, and S. J. Russell, "Distance metric learning with application to clustering with side-information," in Proc. NIPS 15, 2002, pp. 505-512.
22. M. Schultz and T. Joachims, "Learning a distance metric from relative comparisons," in Proc. NIPS 16, 2004, pp. 41-48.
23. J. V. Davis, B. Kulis, P. Jain, S. Sra, and I. S. Dhillon, "Informationtheoretic metric learning," in Proc. ICML, 2007, pp. 209-216.
24. A. Blum and T. Mitchell, "Combining labeled and unlabeled data with co-training," in Proc. COLT, 1998, pp. 92-100.
25. V. Sindhwani, P. Niyogi, and M. Belkin, "A co-regularization approach to semi-supervised learning with multiple views," in Proc. ICML, 2005, pp. 824-831.
26. Z. Zhou and M. Li, "Tri-training: Exploit unlabeled data using three classifiers," IEEE Trans. Knowl. Data Eng., vol. 17, no. 11, pp. 1529-1541, Nov. 2005.
27. S. Goldman and Y. Zhou, "Enhancing supervised learning with unlabeled data," in Proc. ICML, 2000, pp. 327-334.
28. Z. Zhou and M. Li, "Semi-supervised regression with co-training," in Proc. IJCAI, 2005, pp. 908-913.
29. S. Dasgupta, M. Littman, and D. McAllester, "PAC generalization bounds for co-training," in Proc. NIPS 14, 2002, pp. 375-382.
30. M.-F. Balcan, A. Blum, and K. Yang, "Co-training and expansion: Towards bridging theory and practice," in Proc. NIPS 17, 2005, pp. 89-96.
31. W.Wang and Z.-H. Zhou, "Analyzing co-training style algorithms," in Proc. ECML, 2007, pp. 454-465.
32. W. Wang and Z.-H. Zhou, "A new analysis of co-training," in Proc. ICML, 2010, pp. 1135-1142.
33. Z.-H. Zhou and M. Li, "Semi-supervised regression with co-training," in Proc. IJCAI, 2004.
34. M. Belkin, P. Niyogi, and V. Sindhwani, "Manifold regularization: A geometric framework for learning from labeled and unlabeled examples," J. Mach. Learn. Res., vol. 7, pp. 2399-2434, 2006.
35. R. Coifman and S. Lafon, "Diffusion maps," Appl. Comput. Harmon. Anal., 2006.
36. Z.-H. Zhou and M. Li, "Tri-training: Exploiting unlabeled data using three classifiers," IEEE Trans. Knowl. Data Eng., vol. 17, no. 11, pp. 1529-1541, Nov. 2005.
37. C. Aslan, A. Erdem, E. Erdem, and S. Tari, "Disconnected skeleton: Shape at its absolute scale," IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 12, pp. 2188-2203, Dec. 2008.
38. C.-H. Wei, Y. Li, W. Y. Chau, and C.-T. Li, "Trademark image retrieval using synthetic features for describing global shape and interior structure," Pattern Recognit., vol. 42, no. 3, pp. 386-394, Mar. 2009.
39. Z. Tu and A. L. Yuille, "Shape matching and recognition-Using generative models and informative features," in Proc. ECCV, 2004, pp. 195-209.
40. F. R. Schmidt, E. Toeppe, and D. Cremers, "Efficient planar graph cuts with applications in computer vision," in Proc. CVPR, 2009, pp. 351-356.
41. N. Alajlan, M. Kamel, and G. Freeman, "Geometry-based image retrieval in binary image databases," IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 6, pp. 1003-1013, Jun. 2008.
42. P. F. Felzenszwalb and J. Schwartz, "Hierarchical matching of deformable shapes," in Proc. CVPR, 2007, pp. 1-8.
43. L. Lin, K. Zeng, X. Liu, and S. Zhu, "Layered graph matching by composite cluster sampling with collaborative and competitive interactions," in Proc. CVPR, 2009, pp. 1351-1358.
44. C. Xu, J. Liu, and X. Tang, "2D shape matching by contour flexibility," IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 1, pp. 180-186, Jan. 2009.
45. K. Sun and B. Super, "Classification of contour shapes using class segment sets," in Proc. CVPR, 2005, pp. 727-733.
46. X. Bai, W. Liu, and Z. Tu, "Integrating contour and skeleton for shape classification," in Proc. IEEE Workshop NORDIA, 2009, pp. 360-367.
47. M. Daliri and V. Torre, "Shape recognition based on kernel edit distance," Comput. Vis. Image Understand., vol. 114, no. 10, pp. 1097-1103, Oct. 2010.
48. B. Super, "Retrieval from shape databases using chance probability functions and fixed correspondence," Int. J. Pattern Recognit. Artif. Intell., vol. 20, no. 8, pp. 1117-1137, Dec. 2006.
49. E. Attalla and P. Siy, "Robust shape similarity retrieval based on contour segmentation polygonal multiresolution and elastic matching," Pattern Recognit., vol. 38, no. 12, pp. 2229-2241, Dec. 2005.
50. M. Daliri and V. Torre, "Robust symbolic representation for shape recognition and retrieval," Pattern Recognit., vol. 41, no. 5, pp. 1799-1815, May 2008.
51. R. Gonzalez, R.Woods, and S. Eddins, Digital Image Processing Using MATLAB. Englewood Cliffs, NJ: Prentice-Hall, 2004.
52. Y. S. Kim and W. Y. Kim, "Content-based trademark retrieval system using a visually salient feature," Image Vis. Comput., vol. 16, no. 12/13, pp. 931-939, Aug. 1998.
53. D. Nistér and H. Stewénius, "Scalable recognition with a vocabulary tree," in Proc. CVPR, 2006, pp. 2161-2168.
54. J. Sivic and A. Zisserman, "Video Google: A text retrieval approach to object matching in videos," in Proc. ICCV, 2003, pp. 1470-1477.
55. H. Stewénius and D. Nistér, Object recognition benchmark [Online]. Available: http://vis.uky.edu/%7Estewe/ukbench/
56. K. Mikolajczyk and C. Schmid, "Scale and affine invariant interest point detectors," Int. J. Comput. Vis., vol. 60, no. 1, pp. 63-86, Oct. 2004.
57. D. Lowe, "Distinctive image features from scale-invariant key points," Int. J. Comput. Vis., vol. 60, no. 2, pp. 91-110, Nov. 2004.
58. G. Huang, M. Ramesh, T. Berg, and E. Learned-Miller, Labeled faces in the wild: A database for studying face recognition in unconstrained environments Univ. Massachusetts, Amherst, MA, Tech. Rep. 07-49, 2007.
59. T. Ojala, M. Pietikainen, and T. Maenpaa, "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 7, pp. 971-987, Jul. 2002.