WNtags: A Web-Based Tool For Image Labeling And Retrieval With Lexical Ontologies

TL;DR

WNtags is an online image annotation tool leveraging lexical ontologies like WordNet and SUMO for improved image labeling and retrieval, demonstrated on emotionally annotated image datasets.

Contribution

Introduces WNtags, a web-based image annotation system using lexical ontologies for semantic labeling and retrieval, with plans to incorporate affective content analysis.

Findings

Effective image annotation and retrieval using WordNet-based descriptors

Demonstrated utility on the International Affective Picture System dataset

Plans to extend content description with emotional affect

Abstract

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.