Task-based annotation and retrieval for image information management |
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Authors: | Dympna O’Sullivan David C Wilson Michela Bertolotto |
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Affiliation: | (1) School of Engineering and Applied Science, University of Aston, Birmingham, UK;(2) Department of Software and Information Systems, University of North Carolina, Charlotte, NC, USA;(3) School of Computer Science and Informatics, University College Dublin, Dublin, Ireland |
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Abstract: | Continuing advances in digital image capture and storage are resulting in a proliferation of imagery and associated problems
of information overload in image domains. In this work we present a framework that supports image management using an interactive
approach that captures and reuses task-based contextual information. Our framework models the relationship between images
and domain tasks they support by monitoring the interactive manipulation and annotation of task-relevant imagery. During image
analysis, interactions are captured and a task context is dynamically constructed so that human expertise, proficiency and
knowledge can be leveraged to support other users in carrying out similar domain tasks using case-based reasoning techniques.
In this article we present our framework for capturing task context and describe how we have implemented the framework as
two image retrieval applications in the geo-spatial and medical domains. We present an evaluation that tests the efficiency
of our algorithms for retrieving image context information and the effectiveness of the framework for carrying out goal-directed
image tasks. |
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Keywords: | |
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