Abstract
This paper proposes an aggregative query generation which exploits a media document representation called feature term to create a query from multiple media examples, e.g. images. A feature term denotes an interval of one media feature dimension, such as a bin in colour histogram. This approach (1) can easily accumulate features from multiple query examples to generate an efficient query; (2) enables the exploration of text-based retrieval models for multimedia retrieval. Two criteria, minimised chi2 and maximised entropy, are proposed to optimise feature term selection.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the IEEE International Conference on Multimedia and Expo |
| Publisher | IEEE |
| Pages | 850-853 |
| Number of pages | 4 |
| ISBN (Print) | 9781424442904 |
| DOIs | |
| Publication status | Published - 2009 |
Keywords
- query generation
- image retrieval
- multimedia
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Cite this
Ren, R., Halvey, M., & Jose, J. M. (2009). Aggregative query generation. In Proceedings of the IEEE International Conference on Multimedia and Expo (pp. 850-853). IEEE. https://doi.org/10.1109/ICME.2009.5202628