Bridging the gap: Query by semantic example

IEEE Transactions on Multimedia

Volumn 9, Issue 5, 2007, Pages 923-938

  Rasiwasia, Nikhil ^a,b   Moreno, Pedro J ^a,c   Vasconcelos, Nuno ^a,b  

^a IEEE   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c GOOGLE INC   (United States)

Author keywords

Content based image retrieval; Gaussian mixtures; Image similarity; Multiple instance learning; Query by example; Semantic retrieval; Semantic space

Indexed keywords

GAUSSIAN MIXTURES; MULTIPLE INSTANCE LEARNING; SEMANTIC RETRIEVAL; SEMANTIC SPACES;

ERROR ANALYSIS; IMAGE RETRIEVAL; INFORMATION SYSTEMS; PROBABILITY; SEMANTICS; VECTORS;

QUERY PROCESSING;

EID: 34547486835     PISSN: 15209210     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMM.2007.900138     Document Type: Article

References (53)

1. A. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, "Content-based image retrieval: The end of the early years," IEEE Trans. Pattern Anal. Machine Intell., vol. 22, no. 12, pp. 1349-1380, 2000.
2. W. Niblack et al., "The QBIC Project: Querying Images by Content Using Color, Texture, and Shape," in Storage and Retrieval for Image and Video Databases. San Jose, CA: SPIE, Feb. 1993, pp. 173-181.
3. A. Pentland, R. Picard, and S. Sclaroff, "Photobook: Content-based manipulation of image databases," Int. J. Comput. Vis., vol. 18, no. 3, pp. 233-254, Jun. 1996.
4. N. Vasconcelos and M. Kunt, "Content-based retrieval from image databases: Current solutions and future directions," in Proc. Int. Conf. Image Processing, Thessaloniki, Greece, 2001.
5. A. Jain and A. Vailaya, "Image retrieval using color and shape," Pattern Recognit. J., vol. 29, Aug. 1996.
6. J. Smith and S. Chang, VisualSEEk: A. Fully Automated Content-Based Image Query System. Boston, MA: ACM, 1996, pp. 87-98.
7. R. Manmatha and S. Ravela, "A syntatic characterization of appearance and its application, to image retrieval," Proc. SPIE, vol. 3016, 1997.
8. R. Picard, "Digital libraries: Meeting place for high-level and low-level vision," in Proc. Asian Conf. Computer Vision, Singapore, USA, Dec. 1995.
9. M. Szummer and R. Picard, "Indoor-outdoor image classification, " in Proc. Workshop in Content-based Access to Image and Video Databases, Bombay, India, 1998.
10. A. Vailaya, A. Jain, and H. Zhang, "On image classification: City versus landscape," Pattern Recognit., vol. 31, pp. 1921-1936, Dec. 1998.
11. N. Haering, Z. Myles, and N. Lobo, "Locating dedicuous trees," in Proc. Workshop in Content-based Access to Image and Video Libraries, San Juan, Puerto Rico, 1997, pp. 18-25.
12. D. Forsyth and M. Fleck, "Body plans," in Proc. IEEE CVPR, San Juan, Puerto Rico, 1997, pp. 678-683.
13. K. Barnard and D. Forsyth., "Learning the semantics of words and pictures," in Proc. Int. Conf. Computer Vision, Vancouver, 2001, vol. 2, pp. 408-415.
14. P. Duygulu, K. Barnard, N. Freitas, and D. Forsyth., "Object recognition as machine translation: Learning a lexicon for a fixed image vocabulary," in Proc. ECCV, Copenhagen, Denmark, 2002.
15. D. Blei and M. Jordan, "Modeling annotated data," in Proc. ACM SIGIR Conf. Research and Development in IR, 2003.
16. S. Feng, R. Manmatha, and V. Lavrenko, "Multiple Bernoulli relevance models for image and video annotation," in Proc. IEEE CVPR, Washington, DC, 2004.
17. V. Lavrenko, R. Manmatha, and J. Jeon, A model for learning the semantics of pictures. Vancouver, BC, Canada: NIPS, 2003.
18. P. C. H. Kueck and N. Freitas, "A constrained semi-supervised learning approach to data association," in Proc. ECCV, Prague, Czech Republic, 2004.
19. G. Carneiro and N. Vasconcelos, "Formulating semantic image annotation as a supervised learning problem," in Proc. IEEE CVPR, San Diego, 2005.
20. W. Kraaij, P. Over, and A. Smeaton, "TRECVID 2006: An introduction," in Proc. TRECVID, 2006.
21. C. Snoek, M. Worring, D. Koelma, and A. Smeulders, "Learned lexicon-driven interactive video retrieval," in Proc. CIVR, 2006, pp. 11-20.
22. A. Amir et al, "IBM research TRECVID-2005 video retrieval system," in Proc. NIST TRECVID Workshop, Gaithersburg, MD, Nov. 2005.
23. N. Vasconcelos, "Minimum probability of error image retrieval," IEEE Trans. Signal Processing, vol. 52, pp. 2322-2336, Aug. 2004.
24. G. Carneiro, A. Chan, P. Moreno, and N. Vasconcelos, "Supervised learning of semantic classes for image annotation and retrieval," IEEE Pattern Anal. Machine. Intell, vol. 29, no. 3, pp. 394-410, Mar. 2007.
25. G. Salton and J. McGill, Introduction to Modern Information Retrieval. New York: McGraw-Hill, 1983.
26. G. Salton, A. Wong, and C. S. Yang, "A vector space model for automatic indexing," Commun. ACM, vol. 18, no. 11, pp. 613-620, 1975.
27. Y. Kiyoki, T. Kitagawa, and T. Hayama, "A metadatabase system, for semantic image search by a mathematical model of meaning," SIGMOD Rec., vol. 23, no. 4, pp. 34-41, 1994.
28. J. Han and L. Guo, "A new image retrieval system, supporting query by semantics and example," in Proc. Int. Conf. Image. Processing, 2002.
29. N. Vasconcelos and A. Lippman, "Learning over multiple temporal scales in image databases," in Proc. ECCV, Dublin, Ireland, 2000.
30. L. W. Y. Lu, H. J. Zhang, and C. Hu, "Joint semantics and feature based image retrieval using relevance feedback," IEEE Trans. Multimedia, vol. 5, no. 3, pp. 339-347, 2003.
31. X. He, O. King, W. Ma, M. Li, and H. Zhang, "Learning a semantic space from user's relevance feedback for image retrieval," IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 1, pp. 39-48, Jan. 2003.
32. C. S. Lee, W.-Y. Ma, and H. Zhang, "Information embedding based on user's relevance feedback for image retrieval," Proc. SPIE, vol. 3846, pp. 294-304, 1999.
33. I. J. Cox, J. Ghosn, T. V. Papathomas, and P. N. Yianilos, "Hidden annotation in content based image retrieval," in Proc. IEEE CVPR, 1997.
34. J. Smith, M. Naphade, and A. Natsev, "Multimedia semantic indexing using model vectors," ICME, pp. 445-48, 2003.
35. J. R. Smith, C.-Y. Lin, M. R. Naphade, A. Natsev, and B. L. Tseng, "Validity-weighted model vector-based retrieval of video," Proc. SPIE, vol. 5307, pp. 271-279, 2003.
36. M. Z. J. Lu and S.-P. Ma, "Automatic image annotation based-on model space," in Proc. IEEE NLP-KE, 2005.
37. J. Piatt, "Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods," Adv. Large Margin Classifiers, vol. 6.174, 1999.
38. R. Duda, P. Hart, and D. Stork, Pattern Classification. New York: Wiley, 2001.
39. A. Dempster, N. Laird, and D. Rubin, "Maximum-likelihood from incomplete data via the EM algorithm," J. R. Statist. Soc., vol. B-39, 1977.
40. C. Fellbaum, Wordnet: An Electronic Lexical Database. Cambridge, MA: MIT Press, 1998.
41. N. Vasconcelos, "Image indexing with mixture hierarchies," in Proc. IEEE CVPR, Kauai, HI, 2001.
42. A. Gelman, J. Carlin, H. Stern, and D. Rubin, Bayesian Data Analysis. London, U.K.: Chapman & Hall, 1995.
43. N. Vasconcelos, "A unified view of image similarity," in Proc. Int. Conf. Pattern Recognition, Barcelona, Spain, 2000.
44. T. Cover and J. Thomas, Elements of Information Theory. New York: Wiley, 1991.
45. M. Swain and D. Ballard, "Color Indexing," Int. J. Comput. Vis., vol. 7, no. 1, pp. 11-32, 1991.
46. O. Maron and T. Lozano-Perez, A Framework For Multiple Instance Learning, 1998.
47. P. Auer, "On learning from, multi-instance examples: Empirical evaluation of a theoretical approach," in Proc. 14th Int. Conf. Machine Learning, 1997, pp. 21-29.
48. J. Smith, "Image retrieval evaluation," in Proc. IEEE Workshop on Content-Based Access of Image and Video Libraries, 1998.
49. Y. Rui and T. Huang, "Optimizing learning in image retrieval," Proc. IEEE Conf. Computer Vision Pattern Recognition, 2000.
50. H. Muller, S. Marchand-Maillet, and T. Pun, "The truth about corel-evaluation in image retrieval," in Proc. Int. Conf. Image, and Video Retrieval, 2002, pp. 38-49.
51. T. Westerveld and A. P. de Vries, "Experimental evaluation of a generative probabilistic image retrieval model on 'easy' data," in Proc. Multimedia Information Retrieval Workshop, Toronto, ON, Canada, Aug. 2003.
52. S. M. M. Tahaghoghi, J. A. Thorn, and H. E. Williams, "Are two pictures better than one?," in Proc. 12th Australasian Database Conf., Washington, DC, 2001, pp. 138-144.
53. S. Thorpe, D. Fize, and C. Marlot, "Speed of processing in the human visual system," Nature, pp. 520-522, 1996.