CAIM - Context Aware Image Management
|Project manager||Randi Karlsen, associate professor|
Najeeb Elahi, ph.d. candidate
The CAIM project introduces image context-awareness as a means of supporting image-based information retrieval in distributed and mobile environments. An image can be associated with multiple contexts and knowledge of these contexts can enhance the quality of the information retrieval process. We believe that context-awareness can be used for identifying image semantics and relationships, and may thus contribute to closing the semantic gap between user information requests and the shortcomings of current content-based image retrieval techniques.
The CAIM project will focus on research and the development of tools for context-aware image management, where image description, query formulation, retrieval from heterogeneous distributed environments, and ranking are designed for using context information. Important application domains are those requiring image capture and multimodal retrieval in mobile environments.
An objective in the CAIM project is to design a system that is flexible enough to support context-aware image management for a vide variety of applications. To do so, a component-based architecture, using components and component frameworks, will form the basis for a context-aware image management system. The project will develop a prototype implementation of a context-aware image management system and a set of end-user applications that demonstrate the usefulness of CAIM concepts.
Last updated: 23.02.2021 17:15