Relevance feedback for image retrieval in structured multi-feature spaces

Divna Djordjevic; Ebroul Izquierdo

2nd International ICST Conference on Mobile Multimedia Communications

Research Article

Relevance feedback for image retrieval in structured multi-feature spaces

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1145/1374296.1374323,
    author={Divna Djordjevic and Ebroul Izquierdo},
    title={Relevance feedback for image retrieval in structured multi-feature spaces},
    proceedings={2nd International ICST Conference on Mobile Multimedia Communications},
    publisher={ACM},
    proceedings_a={MOBIMEDIA},
    year={2006},
    month={9},
    keywords={Multi-fetaure space kernel methods.},
    doi={10.1145/1374296.1374323}
}

Divna Djordjevic
Ebroul Izquierdo
Year: 2006
Relevance feedback for image retrieval in structured multi-feature spaces
MOBIMEDIA
ACM
DOI: 10.1145/1374296.1374323

Divna Djordjevic¹^,*, Ebroul Izquierdo¹^,*

1: Queen Mary University of London, UK

*Contact email: divna.djordjevic@elec.qmul.ac.uk, ebroul.izquierdo@elec.qmul.ac.uk

Abstract

An approach for content-based image retrieval with relevance feedback based on a structured multi-feature space is proposed. It uses a novel kernel for merging multiple feature subspaces into a complementary space. The kernel exploits nature of the data by assigning appropriate weights for each feature set. The weights are dynamically adapted to user preferences in a relevance feedback scenario.

Keywords: Multi-fetaure space kernel methods.

Published: 2006-09-20
Publisher: ACM

: http://dx.doi.org/10.1145/1374296.1374323

Relevance feedback for image retrieval in structured multi-feature spaces

Abstract

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