Task-based annotation and retrieval for image information management

  • Authors:

  • Dympna O'Sullivan;David C. Wilson;Michela Bertolotto

  • Affiliations:

  • School of Engineering and Applied Science, University of Aston, Birmingham, UK;Department of Software and Information Systems, University of North Carolina, Charlotte, USA;School of Computer Science and Informatics, University College Dublin, Dublin, Ireland

  • Venue:
  • Multimedia Tools and Applications
  • Year:
  • 2011

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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.