Abstract
We query the pictures of Yahoo! News for persons and objects by using the accompanying news captions as an indexing annotation. Our aim is to find these pictures on top of the answer list in which the sought persons or objects are most prominently present. We demonstrate that an appearance or content model based on syntactic, semantic and discourse analysis of the short news text is only useful for finding the best picture of a person of object if the database contains photos each picturing many entities. In other circumstances a simpler bag-of-nouns representation has a good performance. The appearance models are tested in a probabilistic ranking function.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Barnard, K., Duygulu, P., de Freitas, N., Forsyth, D., Blei, D., Jordan, M.I.: Matching Words and Pictures. Journal of Machine Learning Research 3(6), 1107–1135 (2003)
Berg, T.L., Berg, A.C., Edwards, J., Forsyth, D.: Who’s in the Picture? Neural Information Processing Systems, 137–144 (2004)
Coelho, T., Calado, P., Souza, L., Ribeiro-Neto, B.: Image Retrieval Using Multiple Evidence Ranking. Image 16(4), 408–417 (2004)
Croft, W.B., Lafferty, J.: Language Modeling for Information Retrieval. Kluwer Academic Publishers, Boston (2003)
Deschacht, K., Moens, M.: Text Analysis for Automatic Image Annotation. In: Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pp. 1000–1007 (2007)
Deschacht, K., Moens, M.-F.: Efficient Hierarchical Entity Classification Using Conditional Random Fields. In: Proceedings of the 2nd Workshop on Ontology Learning and Population, Sydney, July 2006, pp. 33–40 (2006)
Hsu, W.H., Kennedy, L., Chang, S.-F.: Reranking methods for visual search. IEEE Multimedia Magazine 13(3) (2007)
Mikheev, A.: Automatic Rule Induction for Unknown-Word Guessing. Computational Linguistics 23(3), 405–423 (1997)
Mori, Y., Takahashi, H., Oka, R.: Automatic Word Assignment to Images Based on Image Division and Vector Quantization. In: RIAO 2000 Content-Based Multimedia Information Access, Paris, April 12-14 (2000)
Tollari, S., Glotin, H.: Web image retrieval on ImagEVAL: Evidences on visualness and textualness concept dependency in fusion model. In: ACM International Conference on Image and Video Retrieval (CIVR) (July 2007)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Deschacht, K., Moens, MF. (2008). Finding the Best Picture: Cross-Media Retrieval of Content. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds) Advances in Information Retrieval. ECIR 2008. Lecture Notes in Computer Science, vol 4956. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78646-7_53
Download citation
DOI: https://doi.org/10.1007/978-3-540-78646-7_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78645-0
Online ISBN: 978-3-540-78646-7
eBook Packages: Computer ScienceComputer Science (R0)