Capturing and Reusing Case-Based Context for Image Retrieval
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 1574-1575.
Abstract
Like many other application areas, task-based domains that employ digital imagery are faced with the problem of information overload. Modeling the relationship between images and the tasks being performed is an important step in addressing this problem. We have developed an interactive approach for the capture and reuse of image context information that leverages a measure of a user’s intentions with regard to tasks that they address. We analyze aspects of human-computer interaction information that enables us to infer why image contents are important in a particular context and how specific images have been used to address particular domain goals.
@inproceedings{ijcai2005p251,
title = {Capturing and Reusing Case-Based Context for Image Retrieval},
author = {O'Sullivan, Dympna and McLoughlin, Eoin and Bertolotto, Michela and Wilson, David C.},
booktitle = {Proceedings of the Nineteenth International Joint Conference on
Artificial Intelligence, {IJCAI-05}},
publisher = {International Joint Conferences on Artificial Intelligence},
pages = {1574--1575},
year = {2005},
url = {https://ijcai.org/proceedings/2005/251},
}
TY - CPAPER TI - Capturing and Reusing Case-Based Context for Image Retrieval AU - O'Sullivan, Dympna AU - McLoughlin, Eoin AU - Bertolotto, Michela AU - Wilson, David C. T2 - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05 PB - International Joint Conferences on Artificial Intelligence PY - 2005 SP - 1574 EP - 1575 UR - https://ijcai.org/proceedings/2005/251 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
