WNtags: A Web-Based Tool For Image Labeling And Retrieval With Lexical Ontologies
This tool addresses the need for better image annotation and retrieval methods for researchers and users handling large image repositories, though it appears incremental as it builds on existing lexical ontologies.
The authors tackled the problem of image annotation and retrieval by developing WNtags, an ontology-based online tool that uses WordNet synsets as semantic descriptors, and demonstrated its effectiveness on the International Affective Picture System database for multimedia retrieval tasks.
Ever growing number of image documents available on the Internet continuously motivates research in better annotation models and more efficient retrieval methods. Formal knowledge representation of objects and events in pictures, their interaction as well as context complexity becomes no longer an option for a quality image repository, but a necessity. We present an ontology-based online image annotation tool WNtags and demonstrate its usefulness in several typical multimedia retrieval tasks using International Affective Picture System emotionally annotated image database. WNtags is built around WordNet lexical ontology but considers Suggested Upper Merged Ontology as the preferred labeling formalism. WNtags uses sets of weighted WordNet synsets as high-level image semantic descriptors and query matching is performed with word stemming and node distance metrics. We also elaborate our near future plans to expand image content description with induced affect as in stimuli for research of human emotion and attention.