Task-based annotation and retrieval for image information management


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. © 2010 Springer Science+Business Media, LLC.

Publication DOI: https://doi.org/10.1007/s11042-010-0548-5
Divisions: ?? 50811700Jl ??
Additional Information: The original publication is available at www.springerlink.com
Uncontrolled Keywords: task-based information retrieval,capturing and reusing user context,image manipulation,semantic annotation,case-based reasoning
Publication ISSN: 1573-7721
Last Modified: 02 Jan 2024 18:55
Date Deposited: 30 Apr 2013 15:24
Full Text Link: http://www.spri ... l14312221q5312/
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2011-08-01
Authors: O'Sullivan, Dympna
Wilson, David C.
Bertolotto, Michela



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