NMF-based multimodal image indexing for querying by visual example

CIVR 2010 - 2010 ACM International Conference on Image and Video Retrieval

Volumn , Issue , 2010, Pages 366-373

  González, Fabio A ^a   Caicedo, Juan C ^a   Nasraoui, Olfa ^b   Ben Abdallah, Jaafar ^b  

^a UNIVERSIDAD NACIONAL DE COLOMBIA   (Colombia)

^b UNIVERSITY OF LOUISVILLE   (United States)

Author keywords

Image retrieval; Multimodal analysis; Non negative Matrix Factorization; Query by example

Indexed keywords

BENCHMARK DATASETS; EXPERIMENTAL EVALUATION; IMAGE DATABASE; IMAGE INDEXING; LATENT SEMANTICS; MULTI-MODAL; MULTI-MODAL IMAGE; MULTI-MODAL INTERACTIONS; MULTIMODAL ANALYSIS; NON-NEGATIVE MATRIX FACTORIZATION ALGORITHMS; NONNEGATIVE MATRIX FACTORIZATION; QUERY-BY EXAMPLE; SEMANTIC INDEX; TEXT ANNOTATIONS; VISUAL CONTENT; VISUAL FEATURE;

BLIND SOURCE SEPARATION; FACTORIZATION; IMAGE RETRIEVAL; INDEXING (OF INFORMATION); SEMANTICS;

MATRIX ALGEBRA;

EID: 77955894027     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1816041.1816094     Document Type: Conference Paper

References (28)

1. J. C. Caicedo, J. G. Moreno, E. A. Ninõ, and F. A. Gonzalez. Combining visual features and text data for medical image retrieval using latent semantic kernels. In Proceedings of the ACM MIR'10 International Conference on Multimedia Information Retrieval. ACM, 2010.
2. A. Cemgil. Bayesian inference in non-negative matrix factorisation models. Computational Intelligence and Neuroscience, 2009:4, 2009.
3. M. Cooper and J. Foote. Summarizing video using non-negative similarity matrix factorization. In IEEE Workshop on Multimedia Signal Processing, 2002.
4. R. Datta, D. Joshi, J. Li, and J. Z. Wang. Image retrieval: Ideas, influences, and trends of the new age. ACM Comput. Surv., 40(2):1-60, April 2008.
5. C. Ding, X. He, and H. Simon. On the equivalence of nonnegative matrix factorization and spectral clustering. In Proc. SIAM Data Mining Conf, pages 606-610. Citeseer, 2005.
6. C. Ding, T. Li, and W. Peng. On the equivalence between non-negative matrix factorization and probabilistic latent semantic indexing. Computational Statistics & Data Analysis, 52(8):3913-3927, April 2008.
7. P. Duygulu, K. Barnard, J. de Freitas, and D. Forsyth. Object recognition as machine translation: Learning a lexicon for a fixed image vocabulary. In Computer Vision - ECCV 2002, Lecture Notes in Computer Science, chapter 7, pages 349-354. 2002.
8. X. Fan, X. Xie, Z. Li, M. Li, and W. Ma. Photo-to-search: using multimodal queries to search the web from mobile devices. In Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval, pages 143-150, Hilton, Singapore, 2005. ACM.
9. J. Hare, P. Lewis, P. Enser, and C. Sandom. A linear-algebraic technique with an application in semantic image retrieval. Lecture Notes in Computer Science, 4071:31, 2006.
10. J. S. Hare, S. Samangooei, P. H. Lewis, and M. S. Nixon. Semantic spaces revisited: investigating the performance of auto-annotation and semantic retrieval using semantic spaces. In CIVR '08: Proceedings of the 2008 international conference on Content-based image and video retrieval, pages 359-368, New York, NY, USA, 2008. ACM.
11. J. Jeon, V. Lavrenko, and R. Manmatha. Automatic image annotation and retrieval using cross-media relevance models. In SIGIR '03: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, pages 119-126, New York, NY, USA, 2003. ACM.
12. D. D. Lee and H. S. Seung. Learning the parts of objects by non-negative matrix factorization. Nature, 401(6755):788-791, October 1999.
13. D. D. Lee and H. S. Seung. Algorithms for nonnegative matrix factorization. Advances in Neural Information Processing Systems, 13:556-562, 2001.
14. D. Liang, J. Yang, and Y. Chang. Supervised non-negative matrix factorization based latent semantic image indexing. CHINESE OPTICS LETTERS, 4:272-274, 2006.
15. W. Liu, N. Zheng, and X. Lu. Non-negative matrix factorization for visual coding. In IEEE International Conference on Acoustics, Speech and Signal Processing, 2003.
16. Y. Liu, D. Zhang, G. Lu, and W.-Y. Ma. A survey of content-based image retrieval with high-level semantics. Pattern Recognition, 40:262-282, 2007.
17. J. Magalhães, S. Overell, and S. R "uger. A semantic vector space for query by image example. In ACM SIGIR Conf. on research and development in information retrieval, Multimedia Information Retrieval Workshop. Citeseer, 2007.
18. F. Monay and D. Gatica-Perez. Modeling semantic aspects for cross-media image indexing. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 29(10):1802-1817, August 2007.
19. H. Müller, J. Kalpathy-Cramer, I. Eggel, S. Bedrick, S. Radhouani, B. Bakke, C. Kahn Jr, and W. Hersh. Overview of the clef 2009 medical image retrieval track. CLEF working notes, 2009.
20. E. Nowak, F. Jurie, and B. Triggs. Sampling strategies for bag-of-features image classification. pages 490-503. 2006.
21. N. Rasiwasia, P. J. Moreno, and N. Vasconcelos. Bridging the gap: Query by semantic example. Multimedia, IEEE Transactions on, 9(5):923-938, 2007.
22. N. Rasiwasia and N. Vasconcelos. A study of query by semantic example. In 3rd International Workshop on Semantic Learning and Applications in Multimedia, 2008.
23. A. W. M. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain. Content-based image retrieval at the end of the early years. IEEE Trans. Pattern Anal. Mach. Intell., 22(12):1349-1380, August 2000.
24. J. Tang and P. H. Lewis. Non-negative matrix factorisation for object class discovery and image auto-annotation. In CIVR '08: Proceedings of the 2008 international conference on Content-based image and video retrieval, pages 105-112, New York, NY, USA, 2008. ACM.
25. T. Tsikrika and J. Kludas. Overview of the wikipediamm task at imageclef 2009. In Working Notes for the CLEF 2009 Workshop, 2009.
26. R. C. Veltkamp and M. Tanase. Content-based image retrieval systems: A survey. Technical Report UU-CS-2000-34, Dept. of Computing Science, Utrecht University, 2000.
27. W. Xu, X. Liu, and Y. Gong. Document clustering based on non-negative matrix factorization. In SIGIR '03: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, pages 267-273, New York, NY, USA, 2003. ACM.
28. T. Yeh, K. Grauman, K. Tollmar, and T. Darrell. A picture is worth a thousand keywords: image-based object search on a mobile platform. In CHI '05 extended abstracts on Human factors in computing systems, pages 2025-2028, Portland, OR, USA, 2005. ACM.