Fast image tagging

30th International Conference on Machine Learning, ICML 2013

Volumn , Issue PART 3, 2013, Pages 2311-2319

  Chen, Minmin ^a   Zheng, Alice ^b   Weinberger, Kilian Q ^c  

^a AMAZON   (United States)

^b MICROSOFT RESEARCH   (United States)

^c WASHINGTON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BENCHMARKING; IMAGE RETRIEVAL; LEARNING SYSTEMS;

ASYMPTOTIC COMPLEXITY; AUTOMATIC IMAGE ANNOTATION; IMAGE DESCRIPTORS; NEAREST NEIGHBOR CLASSIFICATION; NOVEL ALGORITHM; ORDERS OF MAGNITUDE; RETRIEVAL ACCURACY; TRAINING AND TESTING;

IMAGE MATCHING;

EID: 84897530662     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (27)

1. Barnard, Kobus, Duygulu, Pinar, Forsyth, David, De Freitas, Nando, Blei, David M, and Jordan, Michael I. Matching words and pictures. The Journal of Machine Learning Research, 3:1107-1135, 2003.
2. Carneiro, G., Chan, A.B., Moreno, P.J., and Vasconcelos, N. Supervised learning of semantic classes for image annotation and retrieval. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 29(3):394-410, 2007. (Pubitemid 46336416)
3. Chen, M., Xu, Z., Weinberger, K., and Sha, F. Marginalized denoising autoencoders for domain adaptation. In ICML '12, pp. 767-774. ACM, New York, NY, USA, July 2012.
4. Cusano, Claudio, Ciocca, Gianluigi, and Schettini, Raimondo. Image annotation using svm. In Electronic Imaging 2004, pp. 330-338. International Society for Optics and Photonics, 2003.
5. Duygulu, P., Barnard, K., De Freitas, J., and Forsyth, D. Object recognition as machine translation: Learning a lexicon for a fixed image vocabulary. Computer VisionECCV 2002, pp. 349-354, 2006.
6. Feng, SL, Manmatha, R., and Lavrenko, V. Multiple bernoulli relevance models for image and video annotation. In Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on, volume 2, pp. II-1002. IEEE, 2004.
7. Fergus, R., Weiss, Y., and Torralba, A. Semi-supervised learning in gigantic image collections. 2009.
8. Grangier, David and Bengio, Samy. A discriminative kernel-based approach to rank images from text queries. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 30(8):1371-1384, 2008.
9. Grubinger, M., Clough, P., Müller, H., and Deselaers, T. The iapr tc-12 benchmark: A new evaluation resource for visual information systems. In International Workshop OntoImage, pp. 13-23, 2006.
10. Guillaumin, M., Mensink, T., Verbeek, J., and Schmid, C. Tagprop: Discriminative metric learning in nearest neighbor models for image auto-annotation. In Computer Vision, 2009 IEEE 12th International Conference on, pp. 309-316. Ieee, 2009.
11. Hafner, J., Sawhney, H.S., Equitz, W., Flickner, M., and Niblack, W. Efficient color histogram indexing for quadratic form distance functions. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 17(7):729-736, 1995.
12. Hertz, Tomer, Bar-Hillel, Aharon, and Weinshall, Daphna. Learning distance functions for image retrieval. In Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on, volume 2, pp. II-570. IEEE, 2004.
13. Jeon, J., Lavrenko, V., and Manmatha, R. Automatic image annotation and retrieval using cross-media relevance models. In Proceedings of the 26th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 119-126. ACM, 2003.
14. Lavrenko, V., Manmatha, R., and Jeon, J. A model for learning the semantics of pictures. NIPS, 2003.
15. Liu, J., Li, M., Liu, Q., Lu, H., and Ma, S. Image annotation via graph learning. Pattern Recognition, 42(2):218-228, 2009.
16. Lowe, D.G. Object recognition from local scale-invariant features. In Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on, volume 2, pp. 1150-1157. Ieee, 1999.
17. Makadia, A., Pavlovic, V., and Kumar, S. A new baseline for image annotation. In ECCV, volume 8, pp. 316-329, 2008.
18. Metzler, D. and Manmatha, R. An inference network approach to image retrieval. Image and video retrieval, pp. 2130-2131, 2004.
19. Monay, Florent and Gatica-Perez, Daniel. Plsa-based image auto-annotation: constraining the latent space. In Proceedings of the 12th annual ACM international conference on Multimedia, pp. 348-351. ACM, 2004.
20. Oliva, A. and Torralba, A. Modeling the shape of the scene: A holistic representation of the spatial envelope. International Journal of Computer Vision, 42(3):145-175, 2001. (Pubitemid 32680801)
21. Schroff, F., Criminisi, A., and Zisserman, A. Harvesting image databases from the web. In Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on, pp. 1-8. IEEE, 2007.
22. Socher, R. and Fei-Fei, L. Connecting modalities: Semi-supervised segmentation and annotation of images using unaligned text corpora. In Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, pp. 966-973. IEEE, 2010.
23. Vedaldi, A. and Zisserman, A. Efficient additive kernels via explicit feature maps. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 34(3):480-492, 2012.
24. Vempala, Santosh S. The random projection method, volume 65. Amer Mathematical Society, 2005.
25. Von Ahn, L. and Dabbish, L. Labeling images with a computer game. In Proceedings of the SIGCHI conference on Human factors in computing systems, pp. 319-326. ACM, 2004.
26. Weinberger, Kilian Q., Slaney, Malcolm, and Van Zwol, Roelof. Resolving tag ambiguity. In Proceeding of the 16th ACM international conference on Multimedia, MM '08, pp. 111-120, New York, NY, USA, 2008. ACM. ISBN 978-1-60558-303-7.
27. Yavlinsky, A., Schofield, E., and Rüger, S. Automated image annotation using global features and robust non-parametric density estimation. Image and video retrieval, pp. 593-593, 2005.