Query analysis is an important phase in image retrieval process especially for ambiguous queries. This paper describes a query analysis process that manages textual and visual queries. The main idea is to select the most appropriate concepts. For the textual part, we extract keywords. Then, we deduce the most relevant concepts related to such keyword by performing a semantic similarity computing based on ontology structure. A similar process is carried out on the visual part based on the associated annotation. The concept set deduced from each part are then merged. Finally, based on a semantic inter-concept graph, we attempt to refine the query by expanding or reweighting the concepts list. Our approach is evaluated in ImagCLEF20121 benchmark. The experiments show encouraging results.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Enhancing query interpretation by combining textual and visual analyses


    Contributors:


    Publication date :

    2013-05-01


    Size :

    330198 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Proper Names Extraction from Fax Images Combining Textual and Image Features

    Likforman-Sulem, L. / Vaillant, P. / Yvon, F. et al. | British Library Conference Proceedings | 2003


    Proper names extraction from fax images combining textual and image features

    Likforman-Sulem, L. / Vaillant, P. / Yvon, F. | IEEE | 2003


    Combining Thermal And Structural Analyses

    Winegar, Steven R. | NTRS | 1990



    Combining Finite Element and Boundary Element Analyses

    Graf, Gerald L. / Gebre-Glorgis, Yoseph | SAE Technical Papers | 1986