Task-based annotation and retrieval for image information management

Dympna O'Sullivan, David C. Wilson, Michela Bertolotto

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Pages (from-to)473-497
Number of pages25
JournalMultimedia Tools and Applications
Issue number2
Publication statusPublished - 1 Aug 2011

Bibliographical note

The original publication is available at www.springerlink.com


  • task-based information retrieval
  • capturing and reusing user context
  • image manipulation
  • semantic annotation
  • case-based reasoning


Dive into the research topics of 'Task-based annotation and retrieval for image information management'. Together they form a unique fingerprint.

Cite this