Abstract
The amount of multimedia documents available in the net stimulates a strong need to explore metadata for improving efficiency of systems’ performance whether commercial, prototypical or open source. This paper provides a framework on image retrieval in cross-language environment based on metadata. Digital images provide visual resources information content that is known as content-based image retrieval (CBIR). We investigate the correlation between query linguistic characteristics that match the visual object collections and the image databases as well as some indexing strategies. Our test set forms a baseline to analyze influence of English and French phenomena on the strategy of browsing the Web for image collections in multilingual environment. Metadata in our experiment is defined as keywords, annotations, image captions or descriptors.
This is a preview of subscription content, log in via an institution to check access.
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
Nack, F.: Multimedia Metadata. In: Liu, L., Ozsu, T. (eds.) Encyclopedia of Database Systems. Springer Science+Business Media (2009)
Callison-Burch, C.: Re-evaluating the role of BLUE in MT Research. In: 11th Conference of the European Chapter of the Association for Computational Linguistics, CACL (2006)
Baneriee, S., Lavie, A.: Meteor: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments. In: Proceedings of Workshop on Intrinsic and Extrinsic Evaluation Measures for MT and Summarization at the 43rd Annual Meeting of the Association of Computational Linguistics, Linguistics, Michigan (2005)
Halliday, M., Rugayia, H.: Cohesion in English. Longman (1976)
Lewis, D.: PC-Based MT; An Illustration of Capabilities in Response to Submitted Test Sentence. MT Review No. 12, The Periodical of the Natural language Translation, Specialist Group of the British Computer Society, Issue No. 12 (2001)
Senellart, P.: Systran Translation Stylesheet (2000)
Lioma, C., Ounis, I.: Deploying part-of-speech patterns to enhance statistical phrase-based machine translation resources. In: ACL 2005: Workshop on Building and Using Parallel Texts – Data-driven Machine Translation and Beyond, pp. 163–166. University of Michigan, Ann Arbor (2005)
Senellart, J., Boitet, C., Romary, L.: Systran New Generation. In: MT Summit IX, pp. 22–26 (2003)
Swan, M.: Practical English Usage. Oxford University Press (2000)
Town, C., Sinclair, D.: Language-based querying of image collections on the basis of an extensible ontology. Image and Vision Computing 22(3), 251–267 (2004)
AltaVista at a Glance – Yahoo, Europe Ltd. London, UK
Grefenstette, G. (ed.): Cross-Language Information Retrieval. Kluwer Academic Publisher Boston, US (1998)
Crestani, F., Lalmas, M., van Rijsbergen, C.: Information Retrieval: Uncertainty and Logics. In: Advanced Models for the Representation and Retrieval of Information. Kluwer Academic Publishers (1999)
Wessa, P.: Free Statistics Software, Office for Research Development and Education (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Mizera-Pietraszko, J. (2014). Metadata Projection for Visual Resources Retrieval. In: Swiątek, J., Grzech, A., Swiątek, P., Tomczak, J. (eds) Advances in Systems Science. Advances in Intelligent Systems and Computing, vol 240. Springer, Cham. https://doi.org/10.1007/978-3-319-01857-7_21
Download citation
DOI: https://doi.org/10.1007/978-3-319-01857-7_21
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01856-0
Online ISBN: 978-3-319-01857-7
eBook Packages: EngineeringEngineering (R0)