We present a new recognition system motivated by human vision for the detection and recognition of objects in real-world images. A computational attention module finds regions of interest in an image and a classifier searches for objects only in these regions. This enables a significantly faster classification. We show how name plates in an office environment are detected by the visual attention module and reliably recognized by the classifier.


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    Titel :

    Simulating visual attention for object recognition


    Beteiligte:
    Frintrop, S. (Autor:in) / Rome, E. (Autor:in)

    Kongress:

    2004


    Erscheinungsdatum :

    2004


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt



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