Using semantic features to improve large-scale visual concept detection

    Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

    3 Sitaatiot (Scopus)

    Abstrakti

    Currently there are many multimedia benchmarks and databases available with a predefined set of concepts for which detectors can be formed or are even already available. One can use these background concepts to form semantic concept vectors for each image or video in the database by concatenating the concept prediction outputs. In this paper we investigate the use of such semantic concept features for detecting novel concepts in two large-scale experiments: the TRECVID 2012 evaluation with 800 hours of video data, and MIRFLICKR with 1 million images. We show that the detection performance can improve significantly over using visual features only. In some applications, computationally expensive kernel classifiers cannot be used in the detection phase, and our experiments show a consistent significant improvement using fast linear classifiers when we replace visual features with the semantic concept feature. We also propose a Self-Organising Map-based method which affords fast training-free detection and intuitive visualisation properties.

    AlkuperäiskieliEnglanti
    Otsikko2014 12th International Workshop on Content-Based Multimedia Indexing, CBMI 2014
    Sivumäärä6
    DOI - pysyväislinkit
    TilaJulkaistu - 2014
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
    TapahtumaInternational Workshop on Content-Based Multimedia Indexing - Klagenfurt, Itävalta
    Kesto: 18 kesäkuuta 201420 kesäkuuta 2014
    Konferenssinumero: 12
    http://www.polytech.univ-savoie.fr/index.php?id=cbmi2012

    Julkaisusarja

    NimiInternational Workshop on Content-Based Multimedia Indexing
    ISSN (painettu)1949-3983
    ISSN (elektroninen)1949-3991

    Workshop

    WorkshopInternational Workshop on Content-Based Multimedia Indexing
    LyhennettäCBMI
    MaaItävalta
    KaupunkiKlagenfurt
    Ajanjakso18/06/201420/06/2014
    www-osoite

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