User Centric Media. First International Conference, UCMedia 2009, Venice, Italy, December 9-11, 2009, Revised Selected Papers

Research Article

Exploiting Complementary Resources for Cross-Discipline Multimedia Indexing and Retrieval

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  • @INPROCEEDINGS{10.1007/978-3-642-12630-7_13,
        author={Virginia Fernandez and Krishna Chandramouli and Ebroul Izquierdo},
        title={Exploiting Complementary Resources for Cross-Discipline Multimedia Indexing and Retrieval},
        proceedings={User Centric Media. First International Conference, UCMedia 2009, Venice, Italy, December 9-11, 2009, Revised Selected Papers},
        proceedings_a={UCMEDIA},
        year={2012},
        month={10},
        keywords={Cross-discipline retrieval multimedia indexing complementary resource analysis particle swarm optimisation},
        doi={10.1007/978-3-642-12630-7_13}
    }
    
  • Virginia Fernandez
    Krishna Chandramouli
    Ebroul Izquierdo
    Year: 2012
    Exploiting Complementary Resources for Cross-Discipline Multimedia Indexing and Retrieval
    UCMEDIA
    Springer
    DOI: 10.1007/978-3-642-12630-7_13
Virginia Fernandez1,*, Krishna Chandramouli1,*, Ebroul Izquierdo1,*
  • 1: Queen Mary, University of London
*Contact email: Virginia.Fernandez@elec.qmul.ac.uk, Krishna.Chandramouli@elec.qmul.ac.uk, Ebroul.Izquierdo@elec.qmul.ac.uk

Abstract

In recent times, the exponential growth of multimedia retrieval techniques has stimulated interest in the application of these techniques to other alien disciplines. Addressing the challenges raised by such cross-discpline multimedia retrieval engines, in this paper we present a multi-user framework in which complementary resources are exploited to model visual semantics expressed by users. The cross-discpline areas include history of technology and news archives. In the framework presented the query terms generated by historians are first analysed and the extraction of corresponding complementary resources are used to index the multimedia news archives. The experimental evaluation is presented on three semantic queries namely wind mills, solar energy and tidal energy.