Coherent phrase model for efficient image near-duplicate retrieval

IEEE Transactions on Multimedia

Volumn 11, Issue 8, 2009, Pages 1434-1445

  Hu, Yiqun ^a   Cheng, Xiangang ^a   Chia, Liang Tien ^a   Xie, Xing ^b   Rajan, Deepu ^a   Tan, Ah Hwee ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b MICROSOFT RESEARCH ASIA   (China)

Author keywords

Bag of word (BoW); Image near duplicate (IND); Quantization; Retrieval; TRECVID

Indexed keywords

BAG OF WORDS; BENCHMARK DATASETS; DESCRIPTORS; EFFECTIVE SOLUTION; FALSE MATCHES; IMAGE DATABASE; LOCAL REGION; QUANTIZATION ERRORS; SPARSE REPRESENTATION; SPATIAL DOMAINS; STATE-OF-THE-ART METHODS; TRECVID; VISUAL PHRASE; VISUAL WORD;

CONTENT BASED RETRIEVAL;

EID: 70450200630     PISSN: 15209210     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMM.2009.2032676     Document Type: Article

References (33)

1. D.-Q. Zhang and S.-F. Chang, "Detecting image near-duplicate by stochastic attribute relational graph matching with learning," in Proc. 12th Annu. ACM Int. Conf. Multimedia, New York, Oct. 2004, pp. 877-884.
2. W.-L. Zhao, C.-W. Ngo, H.-K. Tan, and X. Wu, "Near-duplicate keyframe identification with interest point matching and pattern learning," IEEE Trans. Multimedia, vol.9, no.5, pp. 1037-1048, Aug. 2007.
3. C.-W. Ngo, W.-L. Zhao, and Y.-G. Jiang, "Fast tracking of near-duplicate keyframes in broadcast domain with transitivity propagation," in Proc. 14th Annu. ACM Int. Conf. Multimedia, Santa Barbara, CA, Oct. 2006, pp. 845-854.
4. P. Ghosh, E. D. Gelasca, K. Ramakrisnan, and B. Manjunath, "Duplicate Image Detection in Large Scale Databases," in Platinum Jubilee Volume. Kolkata, India: K. Indian Statistical Inst., 2007.
5. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Comput. Vis., vol.60, no.2, pp. 91-110, Nov. 2004.
6. A. Johnson and M. Hebert, "Using SPIN images for efficient object recognition in cluttered 3D scenes," IEEE Trans. Pattern Anal. Mach. Intell., vol.21, no.5, pp. 433-449, May 1999.
7. S. Lazebnik and M. Raginsky, "Supervised learning of quantizer codebooks by information loss minimization," IEEE Trans. Pattern Anal. Mach. Intell., vol.31, no.7, pp. 1294-1309, Jul. 2009.
8. O. Boiman, E. Shechtman, and M. Irani, "In defense of nearestneighbor based image classificatio," in Proc. IEEE Comput. Soc. Conf. Computer Vision and Pattern Recognition, Anchorage, AK, Jun. 2008.
9. [Online]. Available: http://vireo.cs.cityu.edu.hk/research/ndk/ndk. html.
10. TREC Video Retrieval Evaluation (TRECVID). [Online]. Available: http://wwwnlpir.nist.gov/projects/trecvid/.
11. S. Lazebnik, C. Schmid, and J. Ponce, "Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories," in Proc. IEEE Comput. Soc. Conf. Computer Vision and Pattern Recognition, New York, Jun. 2006, vol.2, pp. 2169-2178.
12. J. Zhu, S. C. Hoi, M. R. Lyu, and S. Yan, "Near-duplicate keyframe retrieval by nonrigid image matching," in Proc. 15th Annu. ACM Int. Conf. Multimedia, Vancouver, BC, Canada, Oct. 2008.
13. D. Nistër and H. Stewënius, "Scalable recognition with a vocabulary tree," in Proc. IEEE Comput. Soc. Conf. Computer Vision and Pattern Recognition, New York, Jun. 2006, vol.2, pp. 2161-2168.
14. K. Grauman and T. Darrell, "The Pyramid Matching Kernel: Discriminative classification with sets of image features," in Proc. IEEE Int. Conf. Computer Vision, Beijing, China, Oct. 2005, vol.2, pp. 1458-1465.
15. K. Grauman and T. Darrell, "Approximate correspondences in high dimensions," in Proc. Advances in Neural Information Processing Systems (NIPS), Cambridge, MA, Dec. 2006, vol.19, pp. 505-512.
16. Y. Ke, R. Sukthankar, and L. Huston, "Efficient near-duplicate detection and sub-image retrieval," in Proc. 12th Annu. ACMInt. Conf. Multimedia, New York, Oct. 2004, pp. 869-876.
17. D. Xu and S.-F. Chang, "Visual event recognition in news video using kernel methods with multi-level temporal alignment," in Proc. IEEE Comput. Soc. Conf. Computer Vision and Pattern Recognition, Minneapolis, MN, Jun. 2007.
18. S. Savarese, J. Winn, and A. Criminisi, "Discriminative object class models of appearance and shape by correlations," in Pro. IEEE Comput. Soc. Conf. Computer Vision and Pattern Recognition, New York, Jun. 2006, vol.2, pp. 2033-2040.
19. H. Ling and S. Soatto, "Proximity distribution kernels for geometric context in category recognition," in Proc. IEEE Int. Conf. Computer Vision, Rio de Janeiro, Brazil, Oct. 2007.
20. J. Sivic and A. Zisserman, "Video data mining using configurations of viewpoint invariant regions," in Proc. IEEE Comput. Soc. Conf. Computer Vision and Pattern Recognition,Washington, DC, Jun. 2004, vol.1, pp. 488-495.
21. J. Yuan, Y. Wu, and M. Yang, "Discovery of collocation patterns: From visual words to visual phrases," in Proc. IEEE Comput. Soc. Conf. Computer Vision and Pattern Recognition, Minneapolis, MN, Jun. 2007.
22. T. Quack, V. Ferrari, B. Leibe, and L. V. Gool, "Efficient mining of frequent and distinctive feature configurations," in Proc. IEEE Int. Conf. Computer Vision, Rio de Janeiro, Brazil, Oct. 2007.
23. J. Zhang, M. Marszałek, S. Lazebnik, and C. Schmid, "Local Features and Kernels for Classification of Texture and Object Categories: An In-Depth Study", Tech. Rep., INRIA, 2005.
24. J. Zhang, M. Marszałek, S. Lazebnik, and C. Schmid, "Local features and kernels for classification of texture and object categories: A comprehensive study," Int. J. Comput. Vis., vol.73, no.2, pp. 213-238, Nov. 2007.
25. 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.
26. S. Lazebnik, C. Schmid, and J. Ponce, "A sparse texture representation using local affine regions," IEEE Trans. Pattern Anal. Mach. Intell., vol.27, no.8, pp. 1265-1278, Aug. 2005.
27. 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.
28. Y. Ke and R. Sukthankar, "PCA-SIFT: A more distinctive representation for local image descriptors," in Proc. IEEE Comput. Soc. Conf. Computer Vision and Pattern Recognition,Washington, DC, Jun. 2004, vol.1, pp. 511-517.
29. L. Cao and L. Fei-Fei, "Spatially coherent latent topic model for concurrent object segmentation and classification," in Proc. IEEE Int. Conf. Computer Vision, Rio de Janeiro, Brazil, Oct. 2007.
30. J. Sivic and A. Zisserman, "Video Google: A text retrieval approach to object matching in videos," in Proc. IEEE Int. Conf. Computer Vision, Nice, France, Oct. 2003, vol.2, pp. 1470-1477.
31. W. Zhao, Y.-G. Jiang, and C.-W. Ngo, "Keyframe retrieval by keypoints: Can point-to-point matching help?," in Proc. Int. Conf. Image and Video Retrieval, Tempe, AZ, Jul. 2006, pp. 72-81.
32. H. Bay, T. Tuytelaars, and L. V. Gool, "SURF: Speeded up robust features," in Proc. Eur. Conf. Computer Vision, Graz, Austria, May 2006.
33. J. J. Lee, LIBPMK: A Pyramid Match Toolkit, MIT Computer Science and Artificial Intelligence Laboratory, 2008, Tech. Rep. MITCSAIL- TR-2008-2017