  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.
