Name
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/s11042-010-0548-5 | Multimedia Tools Appl. |
Keywords | Field | DocType |
Task-based information retrieval,Capturing and reusing user context,Image manipulation,Semantic annotation,Case-based reasoning | Computer vision,Cognitive models of information retrieval,Information overload,Information management,Automatic image annotation,Information retrieval,Computer science,Image retrieval,Digital image,Artificial intelligence,Case-based reasoning,Visual Word | Journal |
Volume | Issue | ISSN |
54 | 2 | 1380-7501 |
Citations | PageRank | References |
2 | 0.36 | 31 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dympna O'Sullivan | 1 | 45 | 11.29 |
| David C. Wilson | 2 | 743 | 67.35 |
| Michela Bertolotto | 3 | 863 | 91.77 |