Work

IAM@ImageCLEFphoto 2009: Experiments on Maximising Diversity using Image Features

Year: 2009

Type: conference-paper

Abstract: This paper describes the diversity enabled retrieval system constructed at Southampton for the ImageCLEFphoto 2009 task. The retrieval system used Terrier as the underlying textual indexing and retrieval system, and combined it with a technique for re-ranking the results by maximising the visual dissimilarity of retrieved images. The results show that our visual re-ranking method does indeed work at increasing the diversity in the top results, however, at the same time it causes a slight drop in precision. The text-based approach designed for handling the 'part 1 topics' of the task is also shown to perform very well.

Source: ePrints Soton (University of Southampton)

Authors: Jonathon Hare, David Dupplaw, Paul Lewis

Language: English

Topic: Image Retrieval and Classification Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: European Commission, Provincia Autonoma di Trento

Award: LivingKnowledge – Facts, Opinions and Bias in Time

OpenAlex ID: W2130250035

FWCI: 0.547

Cites: 10

Cited by: 3

Related to: 10