Image Annotation Refinement Using Web-Based Keyword Correlation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2009

AUTHORS

Ainhoa Llorente , Enrico Motta , Stefan Rüger

ABSTRACT

This paper describes a novel approach that automatically refines the image annotations generated by a non-parametric density estimation model. We re-rank these initial annotations following a heuristic algorithm, which uses semantic relatedness measures based on keyword correlation on the Web. Existing approaches that rely on keyword co-occurrence can exhibit limitations, as their performance depend on the quality and coverage provided by the training data. Additionally, WordNet based correlation approaches are not able to cope with words that are not in the thesaurus. We illustrate the effectiveness of our Web-based approach by showing some promising results obtained on two datasets, Corel 5k, and ImageCLEF2009. More... »

PAGES

188-191

References to SciGraph publications

  • 2008. Web-Based Measure of Semantic Relatedness in WEB INFORMATION SYSTEMS ENGINEERING - WISE 2008
  • 2005. Automated Image Annotation Using Global Features and Robust Nonparametric Density Estimation in IMAGE AND VIDEO RETRIEVAL
  • 2009. Using Second Order Statistics to Enhance Automated Image Annotation in ADVANCES IN INFORMATION RETRIEVAL
  • 2005. Improving Image Annotations Using WordNet in ADVANCES IN MULTIMEDIA INFORMATION SYSTEMS
  • Book

    TITLE

    Semantic Multimedia

    ISBN

    978-3-642-10542-5
    978-3-642-10543-2

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-10543-2_22

    DOI

    http://dx.doi.org/10.1007/978-3-642-10543-2_22

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1046333246


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