Image-Language Association: are we looking at the right features?
Title
Image-Language Association: are we looking at the right features?
Publication Type
Conference Papers
Year of Publication
2006
Authors
Pastra, K
Conference Name
OntoImage Workshop on Language Resources for Content-based Image Retrieval, Language Resources and Evaluation Conference (LREC)
Abstract
The ever growing popularity and availability of multimedia information has rendered automatic image-language association essential in a number of multimedia integration applications. Bridging the gap between the two media requires an appropriate feature-set for describing their common reference; one that will be both distinctive of the entities referred too and feasible to extract automatically from visual media. In this paper, we suggest an alternative –to current approaches- feature set, which has been used in OntoVis, a domain model for a prototype that describes three-dimensional (3D) indoor scenes. We argue that it is worth employing this feature-set in a larger scale for image-language association and investigating the feasibility of doing so and of detecting such features automatically even beyond 3D visual data, in 2D images.
The ever growing popularity and availability of multimedia information has rendered automatic image-language association essential in a number of multimedia integration applications. Bridging the gap between the two media requires an appropriate feature-set for describing their common reference; one that will be both distinctive of the entities referred too and feasible to extract automatically from visual media. In this paper, we suggest an alternative –to current approaches- feature set, which has been used in OntoVis, a domain model for a prototype that describes three-dimensional (3D) indoor scenes. We argue that it is worth employing this feature-set in a larger scale for image-language association and investigating the feasibility of doing so and of detecting such features automatically even beyond 3D visual data, in 2D images.