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    A theory of scene understanding and object recognition.

    11179_Dillon C 1996.pdf (15.15Mb)
    Access Status
    Open access
    Authors
    Dillon, Craig
    Date
    1996
    Supervisor
    Professor Terry Caelli
    Type
    Thesis
    Award
    PhD
    
    Metadata
    Show full item record
    School
    School of Computing
    URI
    http://hdl.handle.net/20.500.11937/194
    Collection
    • Curtin Theses
    Abstract

    This dissertation presents a new approach to image interpretation which can produce hierarchical descriptions of visually sensed scenes based on an incrementally learnt hierarchical knowledge base. Multiple segmentation and labelling hypotheses are generated with local constraint satisfaction being achieved through a hierarchical form of relaxation labelling. The traditionally unidirectional segmentation-matching process is recast into a dynamic closed-loop system where the current interpretation state is used to drive the lower level image processing functions. The theory presented in this dissertation is applied to a new object recognition and scene understanding system called Cite which is described in detail.

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