Context-Driven Image Annotation Using ImageNet

Authors

George E. Noel, Air Force Institute of Technology
Gilbert L. Peterson, Air Force Institute of TechnologyFollow

Document Type

Conference Proceeding

Publication Date

5-2013

Abstract

Image annotation research has demonstrated success on test data for focused domains. Unfortunately, extending these techniques to the broader topics found in real world data often results in poor performance. This paper proposes a novel approach that leverages WordNet and ImageNet capabilities to annotate images based on local text and image features. Signatures generated from ImageNet images based on WordNet synonymous sets are compared using Earth Mover's Distance against the query image and used to rank order surrounding words by relevancy. The results demonstrate effective image annotation, producing higher accuracy and improved specificity over the ALIPR image annotation system. Abstract © AAAI.

Comments

Copyright © 2013, Association for the Advancement of Artificial Intelligence. All rights reserved.

AFIT Scholar furnishes a draft of this conference paper.

Source Publication

26th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2013

Recommended Citation

Noel, G. E., & Peterson, G. L. (2013). Context-driven image annotation using ImageNet. 26th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2013, 462–467.