High-entropy layouts for content-based browsing and retrieval

Ruixuan Wang, Stephen J. McKenna, Junwei Han

    Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

    4 Citations (Scopus)


    Multimedia browsing and retrieval systems can use dimensionality reduction methods to map from high-dimensional content-based feature distributions to low-dimensional layout spaces for visualization. However, this often results in displays in which many items are occluded whilst large regions are empty or only sparsely populated with items. Furthermore, such methods do not take into account the shape of the region of layout space to be populated. This paper proposes a layout method that addresses these limitations. Layout distributions with low Renyi quadratic entropy are penalized since these result in displays in which some regions are over-populated (i.e. many images are occluded), sparsely populated or empty. Experiments using two image datasets and a comparison with two related methods show the effectiveness of the proposed method.
    Original languageEnglish
    Title of host publicationCIVR 2009
    Subtitle of host publicationproceedings of the ACM International Conference on Image and Video Retrieval
    Place of PublicationNew York
    PublisherAssociation for Computing Machinery
    Number of pages8
    ISBN (Print)9781605584805
    Publication statusPublished - 2009
    EventACM International Conference on Image and Video Retrieval 2009 - Santorini Island, Greece
    Duration: 8 Jul 201010 Jul 2010


    ConferenceACM International Conference on Image and Video Retrieval 2009
    Abbreviated titleCIVR 2009
    CitySantorini Island
    Internet address


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