Feature aggregating hashing for image copy detection

World Wide Web

Volumn 19, Issue 2, 2016, Pages 217-229

  Yan, Lingyu ^a   Zou, Fuhao ^b   Guo, Rui ^c   Gao, Lianli ^d   Zhou, Ke ^e   Wang, Chunzhi ^a  

^a HUBEI UNIVERSITY OF TECHNOLOGY   (China)

^b HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^c SOUTHEAST UNIVERSITY   (China)

^d UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^e HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Feature aggregation; Image copy detection; Machine learning base hashing; Visual words

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS;

CONTENT BASED IMAGES; FEATURE AGGREGATION; IMAGE COPY DETECTION; IMAGE REPRESENTATIONS; LARGE-SCALE DATABASE; NEIGHBORHOOD STRUCTURE; ROBUST FEATURE EXTRACTIONS; VISUAL WORD;

FEATURE EXTRACTION;

EID: 84958115547     PISSN: 1386145X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11280-015-0346-0     Document Type: Article

References (23)

1. Berrani, S. A., Amsaleg, L., Gros, P.: Robust content-based image searches for copyright protection. Int. Workshop Multimed. Databases, 70–77 (2003)
2. Cai, D., Xiaofei, H., Jiawei, H.: SRDA: An efficient algorithm for large-scale discriminant analysis. IEEE Trans. Knowl. Data Eng. 20(1), 1–12 (2008)
3. Foo, J.J., Sinha, R.: Pruning sift for scalable near-duplicate image matching. In: Proceedings of the Eighteenth Conference on Australasian Database, pp. 63–71 (2007)
4. Gong, Y., Lazebnik, S.: Iterative quantization: a procrustean approach to learning binary codes. In: Proceedings of the IEEE Computer Conference on Computer Vision and Pattern Recognition, pp. 817–824 (2011)
5. Han, Y, Wu, F., Tian, Q., Zhuang, Y.: Image annotation by input-output structural grouping sparsity. IEEE Trans. Image Process. 21(6), 3066–3079 (2012)
6. Han, Y., Wu, F., Tao, D., Shao, J., Zhuang, Y., Jiang, J.: Sparse unsupervised dimensionality reduction for multiple view data. IEEE Trans. Circ. Syst. Video Technol. 22(10), 1485–1496 (2012)
7. Han, Y., Yang, Y., Zhou, X.: Co-regularized ensemble for feature selection. Int. Joint Conf. Artif. Intell., 2013 (2013)
8. Han, Y., Yang, Y., Yan, Y., Ma, Z., Sebe, N., Zhou, X.: Semi-supervised feature selection via spline regression for video semantic recognition. IEEE Trans. Neural Netw. Learn. Syst. (IEEE T-NNLS) 26(2), 252–264 (2015)
9. Jegou, H., Perronnin, F., Douze, M., et al.: Aggregating local image descriptors into compact codes. IEEE Trans. Pattern Anal. Mach. Intell., 1704–1716 (2012)
10. Ke, Y., Sukthankar, R., Huston Larry, L.: Efficient near-duplicate and subimage retrieval. ACM Multimed, 869–876 (2004)
11. Kulis, B., Grauman, K.: Kernelized locality-sensitive hashing for scalable image search. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2130–2137 (2009)
12. Kokiopoulou, E., Chen, J., Saad, Y.: Trace optimization and eigenproblems in dimension reduction methods. Numer. Linear Algebra Appl. 18(3), 565–602 (2011)
13. Li, P., Wang, M., Cheng, J., Xu, C., Lu, H.: Spectral hashing with semantically consistent graph for image indexing. IEEE Trans Multimed 15(1), 141–152 (2013)
14. Poullot, S., Crucianu, M., Buisson, O.: Scalable mining of large video databases using copy detection. ACM Multimed, 61–70 (2008)
15. Tang, Z., Wang, S., Zhang, X., Wei, W., Su, S.: Robust image hashing for tamper detection using non-negative matrix factorization. J. Ubiquitous Convergence Technol 2(1), 18–26 (2008)
16. Weiss, Y., Torralba, A., Fergus, R.: Spectral hashing. Adv. Neural Inf. Process. Syst, 1753–1760 (2009)
17. Weiss, Y., Torralba, A., Fergus, R.: Spectral hashing. In: Proceedings of the 2008 Conference Advances in Neural Information Processing Systems, pp. 1753–1760 (2009)
18. Yan, Y., Liu, G., Wang, S., Zhang, J., Zheng, K.: Graph-based clustering and ranking for diversified image search. Multimed. Systemsation. doi:10.1007/s00530-014-0419-4 (2014)
19. Yang, Y., Nie, F., Xu, D., Luo, J., Zhuang, Y., Pan, Y.: A multimedia retrieval framework based on semi-supervised ranking and relevance feedback. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 34(5), 723–742 (2012)
20. Yang, Y., Ma, Z., Xu, Z., Yan, S., Hauptmann, A.: How related exemplars help complex event detection in web videos? In: Proceedings of the 2013 IEEE International Conference on Computer Vision, pp. 1–8 (2013)
21. Yang, Y., Ma, Z., Nie, F., Chang, X., Hauptmann, A.: Multi-class active learning by uncertainty sampling with diversity maximization. Int. J. Comput. Vis. (IJCV). doi:10.1007/s11263-014-0781-x (2014)
22. Zhang, D., Wang, J., Cai, D., Lu, J.: Self-taught hashing for fast similarity search. In: Proceedings of the 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 18–25 (2010)
23. Zou, F., Feng, H., Ling, H., Liu, C., Lingyuyan, Li, P., Li, D.: Nonnegative sparse coding induced hashing for image copy detection. Neurocomputing (Elsevier Academic Press) 105(1), 81C89 (2013)