Social negative bootstrapping for visual categorization

Proceedings of the 1st ACM International Conference on Multimedia Retrieval, ICMR'11

Volumn , Issue , 2011, Pages

  Li, Xirong ^a   Snoek, Cees G M ^a   Worring, Marcel ^a   Smeulders, Arnold W M ^a  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

negative bootstrapping; social tagged examples

Indexed keywords

ADAPTIVE SAMPLING; DE FACTO STANDARD; HUMAN INTERACTIONS; LABELING PROCEDURES; LEARNING PROCESS; NEGATIVE BOOTSTRAPPING; NEGATIVE EXAMPLES; POSITIVE EXAMPLES; RANDOM SAMPLING; SOCIAL-TAGGED EXAMPLES; TRAINING EXAMPLE; VISUAL CATEGORIZATION;

VIRTUAL REALITY;

EID: 79959728335     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1991996.1992008     Document Type: Conference Paper

References (32)

1. H. Bay, A. Ess, T. Tuytelaars, and L. van Gool. Speeded-up robust features (SURF). Comput. Vis. Image Underst., 110(3):346-359, 2008.
2. L. Breiman. Bagging predictors. Mach. Learn., 24(2):123-140, 1996.
3. C.-C. Chang and C.-J. Lin. LIBSVM: a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.
4. T.-S. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y.-T. Zheng. NUS-WIDE: A real-world web image database from National University of Singapore. In CIVR, 2009.
5. R. Cilibrasi and P. Vitanyi. The Google similarity distance. In IEEE Trans. on Knowl. and Data Eng., 2004.
6. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei. ImageNet: A large-scale hierarchical image database. In CVPR, 2009.
7. M. Everingham, L. van Gool, C. Williams, J. Winn, and A. Zisserman. The PASCAL Visual Object Classes Challenge 2008 Results. http://www.pascal-network. org/challenges/VOC/voc2008/workshop/index.html.
8. Y. Freund and R. Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. Syst. Sci., 55:119-139, 1997.
9. N. Japkowicz and S. Stephen. The class imbalance problem: A systematic study. Intell. Data Anal., 6(5):429-449, 2002.
10. L. Kennedy, S.-F. Chang, and I. Kozintsev. To search or to label?: Predicting the performance of search-based automatic image classifiers. In ACM MIR, 2006.
11. X. Li and C. Snoek. Visual categorization with negative examples for free. In ACM MM, 2009.
12. X. Li, C. Snoek, and M. Worring. Learning social tag relevance by neighbor voting. IEEE Trans. MM, 11(7):1310-1322, 2009.
13. B. Liu, Y. Dai, X. Li, W. Lee, and P. Yu. Building text classifiers using positive and unlabeled examples. In ICDM, 2003.
14. D. Liu, X.-S. Hua, and H.-J. Zhang. Content-based tag processing for internet social images. Multimedia Tools Appl., 51:723-738, 2011.
15. G. Miller. WordNet: a lexical database for english. Commun. ACM, 38(11):39-41, 1995.
16. M. Naphade, J. Smith, J. Tešić, S.-F. Chang, W. Hsu, L. Kennedy, A. Hauptmann, and J. Curtis. Large-scale concept ontology for multimedia. IEEE MM, 13(3):86-91, 2006. (Pubitemid 44263760)
17. A. Natsev, M. Naphade, and J. Tešić. Learning the semantics of multimedia queries and concepts from a small number of examples. In ACM MM, pages 598-607, 2005.
18. B. Russell, A. Torralba, K. Murphy, and W. Freeman. LabelMe: A database and web-based tool for image annotation. Int. J. Comput. Vision, 77(1-3):157-173, 2008.
19. F. Schroff, A. Criminisi, and A. Zisserman. Harvesting image databases from the web. IEEE Trans. Pattern Anal. Mach. Intell., 2010. in press.
20. A. Sun and S. Bhowmick. Quantifying tag representativeness of visual content of social images. In ACM MM, 2010.
21. D. Tax. One-class classification. PhD thesis, Delft University of Technology, 2001.
22. S. Tong and E. Chang. Support vector machine active learning for image retrieval. In ACM MM, 2001.
23. A. Torralba, R. Fergus, and W. Freeman. 80 million tiny images: A large data set for nonparametric object and scene recognition. IEEE Trans. Pattern Anal. Mach. Intell., 30(11):1958-1970, 2008.
24. J. Uijlings, A. Smeulders, and R. Scha. Real-time visual concept classification. IEEE Trans. MM, 12(7):665-681, 2010.
25. A. Ulges, C. Schulze, M. Koch, and T. Breuel. Learning automatic concept detectors from online video. Comput. Vis. Image Underst., 114(4):429-438, 2010.
26. V. Vapnik. The Nature of Statistical Learning Theory. Springer-Verlag, 2000.
27. P. Viola and M. Jones. Robust real-time face detection. Int. J. Comput. Vision, 57:137-154, 2004.
28. X.-J. Wang, L. Zhang, X. Li, and W.-Y. Ma. Annotating images by mining image search results. IEEE Trans. Pattern Anal. Mach. Intell., 30(11):1919-1932, 2008.
29. R. Yan, A. Hauptmann, and R. Jin. Negative pseudo-relevance feedback in content-based video retrieval. In ACM MM, 2003.
30. K. Yanai and K. Barnard. Probabilistic web image gathering. In ACM MIR, 2005.
31. G. Zhu, S. Yan, and Y. Ma. Image tag refinement towards low-rank, content-tag prior and error sparsity. In ACM MM, 2010.
32. S. Zhu, G. Wang, C.-W. Ngo, and Y.-G. Jiang. On the sampling of web images for learning visual concept classifiers. In CIVR, 2010.