Indexing or retrieving information from a database of images in response to a query is an important problem in the on-line maintenance of large volumes of documents depicting images, graphics and text. A key component of image indexing is the selection of image regions that are likely to contain the queried object. In this paper we propose attentional selection as a paradigm for selection during image indexing. Specifically, we present an implementation of a model of attentional selection to perform indexing in the domain of technical manual documents depicting line drawing images of physical equipment. The indexing system developed selects regions containing a 3D machine part in relevant pages of the manual in response to a query describing the part. Model-based object recognition then confirms the presence of the part at that location by solving for the pose of the queried object.
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