Attribute-augmented semantic hierarchy: Towards bridging semantic gap and intention gap in image retrieval

MM 2013 - Proceedings of the 2013 ACM Multimedia Conference

Volumn , Issue , 2013, Pages 33-42

  Zhang, Hanwang ^a   Zha, Zheng Jun ^a,b   Yang, Yang ^a   Yan, Shuicheng ^a   Gao, Yue ^a   Chua, Tat Seng ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b INSTITUTE OF INTELLIGENT MACHINES   (China)

Author keywords

Attribute; Image retrieval; Semantic hierarchy

Indexed keywords

ATTRIBUTE; CONTENT-BASED IMAGE RETRIEVAL SYSTEM; LARGE-SCALE DATUM; SEARCH INTENTS; SEMANTIC AFFINITY; SEMANTIC HIERARCHIES; SEMANTIC LEVELS; SEMANTIC SIMILARITY;

CONTENT BASED RETRIEVAL; IMAGE RETRIEVAL;

SEMANTICS;

EID: 84887498863     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2502081.2502093     Document Type: Conference Paper

References (40)

1. M. Crucianu, M. Ferecatu, and N. Boujemaa. Relevance feedback for image retrieval: A short survey. DELOS2 Report, 2004.
2. R. Datta, D. Joshi, J. Li, and J. Wang. Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys, 2008.
3. J. Deng, A. C. Berg, and L. Fei-Fei. Hierarchical semantic indexing for large scale image retrieval. In CVPR, 2011.
4. 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.
5. T. Deselaers and V. Ferrari. Visual and semantic similarity in imagenet. In CVPR, 2011.
6. M. Douze, A. Ramisa, and C. Schmid. Combining attributes and fisher vectors for efficient image retrieval. In CVPR, 2011.
7. J. Fan, Y. Gao, and H. Luo. Integrating concept ontology and multitask learning to achieve more effective classifier training for multilevel image annotation. TIP, 2008.
8. A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth. Describing objects by their attributes. In CVPR, 2009.
9. X. Felix, R. Ji, M. Tsai, G. Ye, and S. Chang. Weak attributes for large-scale image retrieval. In CVPR, 2012.
10. C. Fellbaum. Wordnet. Theory and Applications of Ontology: Computer Applications, 2010.
11. A. Hanjalic, C. Kofler, and M. Larson. Intent and its discontents: The user at the wheel of the online video search engine. In MM, 2012.
12. A. Jaimes and S. fu Chang. A conceptual framework for indexing visual information at multiple levels. In SPIE Internet Imaging, 2000.
13. A. Kovashka, D. Parikh, and K. Grauman. Whittlesearch: Image search with relative attribute feedback. In CVPR, 2012.
14. T. Leung and J. Malik. Representing and recognizing the visual appearance of materials using three-dimensional textons. IJCV, 2001.
15. M. Lew, N. Sebe, C. Djeraba, and R. Jain. Content-based multimedia information retrieval: State of the art and challenges. TOMCCAP, 2006.
16. D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 2004.
17. Z. Ma, Y. Yang, Z. Xu, S. Yan, N. Sebe, and A. G. Hauptmann. Complex event detection via multi-source video attributes. In CVPR, 2012.
18. M. Marszalek and C. Schmid. Semantic hierarchies for visual object recognition. In CVPR, 2007.
19. F. Monay and D. Gatica-Perez. On image auto-annotation with latent space models. In MM, 2003.
20. M. Naphade, J. R. Smith, J. Tesic, S.-F. Chang, W. Hsu, L. Kennedy, A. Hauptmann, and J. Curtis. Large-scale concept ontology for multimedia. Multimedia, IEEE, 2006.
21. P. Over, G. Awad, M. Michel, J. Fiscus, G. Sanders, B. Shaw, W. Kraaij, A. F. Smeaton, and G. Quĺeenot. Trecvid 2012 - An overview of the goals, tasks, data, evaluation mechanisms and metrics. In TRECVID, 2012.
22. D. Parikh and K. Grauman. Interactively building a discriminative vocabulary of nameable attributes. In CVPR, 2011.
23. Y. Rui, T. S. Huang, and S.-F. Chang. Image retrieval: Current techniques, promising directions, and open issues. JVCIR, 1999.
24. Y. Rui, T. S. Huang, M. Ortega, and S. Mehrotra. Relevance feedback: A power tool for interactive content-based image retrieval. TCSVT, 1998.
25. O. Russakovsky and L. Fei-Fei. Attribute learning in large-scale datasets. In ECCV, 2010.
26. W. J. Scheirer, N. Kumar, P. N. Belhumeur, and T. E. Boult. Multi-attribute spaces: Calibration for attribute fusion and similarity search. In CVPR, 2012.
27. N. Sebe, M. S. Lew, X. Zhou, T. S. Huang, and E. M. Bakker. The state of the art in image and video retrieval. In Image and Video Retrieval. 2003.
28. A. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain. Content-based image retrieval at the end of the early years. TPAMI, 2000.
29. J. R. Smith and S.-F. Chang. Visualseek: A fully automated content-based image query system. In MM, 1997.
30. C. G. Snoek, B. Huurnink, L. Hollink, M. De Rijke, G. Schreiber, and M. Worring. Adding semantics to detectors for video retrieval. TMM, 2007.
31. C. G. Snoek and M. Worring. Concept-based video retrieval. FTIR, 2008.
32. Y. Song, M. Zhao, J. Yagnik, and X. Wu. Taxonomic classification for web-based videos. In CVPR, 2010.
33. D. Tao, X. Tang, X. Li, and X. Wu. Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval. TPAMI, 2006.
34. S. Tong and E. Chang. Support vector machine active learning for image retrieval. In MM, 2001.
35. N. Verma, D. Mahajan, S. Sellamanickam, and V. Nair. Learning hierarchical similarity metrics. In CVPR, 2012.
36. J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong. Locality-constrained linear coding for image classification. In CVPR, 2010.
37. K. Q. Weinberger, J. Blitzer, and L. K. Saul. Distance metric learning for large margin nearest neighbor classification. In NIPS, 2006.
38. Z.-J. Zha, L. Yang, T. Mei, M. Wang, and Z. Wang. Visual query suggestion. In MM, 2009.
39. H. Zhang, Z.-J. Zha, S. Yan, J. Bian, and T.-S. Chua. Attribute feedback. In MM, 2012.
40. K. Zhang, I. W. Tsang, and J. T. Kwok. Maximum margin clustering made practical. TNN, 2009.